Social Impact of the Regional Financial Crisis in the Philippines

Philippine Institute for Development Studies

Social Impact of the Regional Financial Crisis in the Philippines Celia M. Reyes, Rosario G. Manasan, Aniceto C. Orbeta, Jr. and Generoso G. de Guzman DISCUSSION PAPER SERIES NO. 99-14

The PIDS Discussion Paper Series constitutes studies that are preliminary and subject to further revisions. They are being circulated in a limited number of copies only for purposes of soliciting comments and suggestions for further refinements. The studies under the Series are unedited and unreviewed.

The views and opinions expressed are those of the author(s) and do not necessarily reflect those of the Institute.

Not for quotation without permission from the author(s) and the Institute.

August 1999 (Revised) For comments, suggestions or further inquiries please contact: The Research Information Staff, Philippine Institute for Development Studies 3rd Floor, NEDA sa Makati Building, 106 Amorsolo Street, Legaspi Village, Makati City, Philippines Tel Nos: 8924059 and 8935705; Fax No: 8939589; E-mail: publications@pidsnet.pids.gov.ph Or visit our website at http://www.pids.gov.ph

SOCIAL IMPACT OF THE REGIONAL FINANCIAL CRISIS IN THE PHILIPPINES OUTLINE

Page EXECUTIVE SUMMARY I.

II.

III.

IV.

V.

INTRODUCTION

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1.

2.

3.

4.

5.

1 2 3 4 5

Specific Objectives Framework of Analysis Data Sources and Methodology Background on the Origin and Causes of the Crisis Review of Previous Studies Done

ECONOMIC AND HUMAN DEVELOPMENT SITUATION PRIOR TO THE CRISIS

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1. Economic Situation 2. Human Development Situation

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ECONOMIC IMPACT OF THE CRISIS

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1.

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3.

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6.

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11 11 12 13 14 14 15 15

Exchange Rate Interest Rates Economic Growth Inflation Unemployment Trade Gap Balance of Payments and International Reserves Position Budget Deficit

FISCAL IMPACT OF THE CRISIS

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1. National Government Revenues and Expenditures 2. LGU Revenues and Expenditures

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SOCIAL IMPACT OF THE CRISIS

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24 30 37 44 49

Labor Market Poverty and Income Distribution Human Development Vulnerable Groups Social Fabric

VI.

VII.

RESPONSES TO THE CRISIS AND HOUSEHOLD COPING MECHANISMS

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50 56 57 65

Government Business Households Community

ASSESSMENT OF EXISTING MONITORING SYSTEMS

VIII. CONCLUSION AND RECOMMENDATIONS FIGURES TABLES REFERENCES

66 71

LIST OF FIGURES AND TABLES

Figure II.1 Figure II.2 Figure II.3 Figure III.1 Figure III.2 Figure III.3 Figure III.4 Figure III.5 Figure III.6

Real GDP Growth Rates, 1981 – 1996 Real Per Capita GNP, 1981 – 1997 Fiscal Position, 1981 – 1996 Monthly Exchange Rates, 1997 – 1999 Monthly 91-Day Treasury Bill Rates, 1997 – 1999 Monthly Lending Rates, 1997 – 1998 Inflation Rate, 1997 – 1999 Trade Balance, 1990 – 1998 Gross International Reserves, 1997 – 1999

Table I.1 Table I.2 Table I.3

Exchange Rates for South East Asian Countries, 1997 - 1998 Direct and Portfolio Investments, 1990 – 1996 External Debt and Debt Service Burden as Percent of GDP for Selected East Asian Countries, 1990 – 1996 Real GDP Growth Rates in Selected East Asian Countries, 1990 – 1996 Inflation, Interest Rate, Exchange Rate, 1981 – 1996 Balance of Payments, Gross International Reserves, External Debt, 1981 – 1996 Gross National Income Per Capita (In constant 1987 US$), 1960 – 1994 Unemployment Rates of Selected Asian Countries, 1971 – 1995 Poverty in Selected Asian Countries Summary Statistics, 1975 – 1995 Human Development Indicators of Selected ASEAN Countries, 1988 1995 Human Development Ranking of Selected ASEAN Countries, 1988 - 1995 GDP and Sectoral Growth Trends, 1980 – 1998 GNP by Expenditure Shares, 1990 – 1998 Unemployment and Underemployment Rate, 1990 – 1998 Imports by Commodity, 1995 – 1998 Exports by Commodity, 1995 – 1998 Balance of Payments (In million of US$), 1995 – 1998 National Government Revenues as Proportion of GNP, 1986 - 1998 National Government Deficit as Proportion of GNP, 1986 - 1998 1997/1998 Revenue Programs (In Million Pesos) Growth Rate of National Government Expenditures, by Sectoral Classification, 1975 – 1999 National Government Expenditures as a Proportion of GNP, by Sectoral Classification, 1975 – 1999 Evolution of 1998 National Government Budget (In Million Pesos) Per Capita National Government Expenditure in 1985 Prices, 1996 - 1999 Department of Health, 1998 Appropriations, Allotments & Obligations (As of September 30, 1998) Department of Health, 1998 Appropriations, Allotments & Obligations (As of December 30, 1998)

Table II.1 Table II.2 Table II.3 Table II.4 Table II.5 Table II.6 Table II.7 Table II.8 Table III.1 Table III.2 Table III.3 Table III.4 Table III.5 Table III.6 Table IV.1 Table IV.2 Table IV.3 Table IV.4 Table IV.5 Table IV.6 Table IV.7 Table IV.8 Table IV.9

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Table IV.10 Table IV.11 Table IV.12 Table IV.13 Table IV.14 Table V.1 Table V.2 Table V.3 Table V.4 Table V.5 Table V.6 Table V.7 Table V.8 Table V.9 Table V.10 Table V.11 Table V.12 Table V.13 Table V.14 Table V.15 Table V.16 Table V.17 Table V.18 Table V.19 Table V.20

DECS, 1998 Appropriations, Allotments & Obligations (For the period ending December 31, 1998) DSWD, 1998 Appropriations, Allotments & Obligations (As of September 30, 1998) Percentage Change in Locally Sourced Revenue, 1997 – 1998 Expenditure Share by Sector, Appropriations Versus Obligations General Fund (Current Account Only), 1998 Real Per Capita LGU Spending, 1997 – 1998 Current General Funds (in 1997 Prices) Labor Force Participation Rate by Age Group, Urban-Rural, 1995 – 1999 Labor Force by Employment Status, Urban-Rural, 1995 – 1999 Employment by Major Industry Group (In Thousand Persons), 1991 – 1998 Employed Workers by Age Group, Urban-Rural, January 19996 – October 1998 Total Employed by Highest Educational Attainment, January 1996 – October 1998 Deployed Overseas Filipino Workers, 1991 - 1998 Deployed Landbased Overseas Filipino Workers by Country of Destination, 1991 - 1998 Remittances of Overseas Filipino Workers – by Destination (In Thousand US Dollars), 1990 - 1998 Number of Firms that Closed or Retrenched Due to Economic Reasons, Semestral Data, 1996 – 1998 Number of Firms that Closed or Retrenched Due to Economic Reasons, Regional Annual Data, 1996 – 1998 Number of Firms that Closed or Retrenched Due to Economic Reasons, Regional Annual Data, 1996 – 1998 Number of Workers Affected by, Philippines, 1995 – 1998 Impact on Employment and Labor Market (Percent of Communities), January 1999 Distribution of Persons 15 Years and Over by Occupation, by Sex, All Communities, January 1999 Distribution of Persons 15 Years and Over by Occupation, Sex and Type of Communities, January 1999 Reasons For Not Working, All Communities, January 1999 Impact of the Financial Crisis on Income of Households by Decile, 1998 Comparative Per Capita Income Using 1997 FIES and 1998 APIS Comparative Annual Income Per Family Using the APIS and 1997 FIES,

by Income Decile Inflation Rate by Major Commodity Group, 1991 – 1998

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Table V.21 Table V.22

Inflation Rate by Region, 1991 – 1998 Changes in Household Consumption and Expenditures, All Communities, January 1999

Table V.23

Changes in Household Consumption and Expenditures by Type of Communities, January 1999 Comparative Average Monthly Income Using the APIS and 1997 FIES,

by Income Decile Immunization Program Performance, 1996 - 1998 Nutrition Program Performance, 1996 – 1998 Contraceptive Prevalence Rate for Currently Married Women 15 – 49 Years Old, 1993, 1996 - 1998 Family Program Performance, 1996 – 1998 Reasons by Changing School by Type of Community, January 1999 Elementary Enrolment by Region, 1996 – 1999 Secondary Enrolment by Region, 1996 – 1999 Elementary Drop-Out Rate by Region, 1996 – 1999 Secondary Drop-Out Rate by Region, 1996 – 1999 Distribution of Persons 15 Years and Over Who Changed Work in the Past Two Years by Place of Work, All Community, January 1999 Distribution of Persons 15 Years and Over Who Changed Work in the Past Two Years by Place of Work and Type of Community, January 1999 Reasons for Leaving Last Job, All Communities, January 1999 Reasons for the Return of Migrant Household Member, All Communities, January 1999 Reasons for the Return of Migrant Family Member by Type of Community, January 1999 Distribution of Households Getting Financial Support from Migrant Family Members by Percent Share to Total Household Income, All Communities, January 1999 Impact on Families of Migrant Workers (Percent of Communities), January 1999 Household Response to Employment and Labor Market Problems (Percent of Communities), January 1999 Changes in Household Budgeting and Poverty and Well-Being Assessment by Type of Community, 1997 - 1998 Information on Credit and Safety Nets, All Communities, January 1999 Information on Credit and Safety Nets by Type of Community, January 1999 Profile of Income Distribution and Consumption Households, January

Table V.24 Table V.25 Table V.26 Table V.27 Table V.28 Table V.29 Table V.30 Table V.31 Table V.32 Table V.33 Table VI.1 Table VI.2 Table VI.3 Table VI.4 Table VI.5 Table VI.6

Table VI.7 Table VI.8 Table VI.9 Table VI.10 Table VI.11

Table VI.12 1999 Table VI.13 Income Distribution Profile of Households by Type of Community, January 1999

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SOCIAL IMPACT OF THE REGIONAL FINANCIAL CRISIS IN THE PHILIPPINES EXECUTIVE SUMMARY

• The Philippines, having been integrated into the global economy, was not spared from the financial crisis that hit Asia in July 1997. Just like other countries in the region, the country became increasingly vulnerable as it absorbed a portion of the massive portfolio investments that flowed into the region two to three years before the crisis.

The large capital inflows strengthened the domestic currency even as the country’s trade deficit widened.

• Prior to the crisis, the Philippines experienced significant economic and human development improvements as it benefited from the various policy reforms instituted in 1991-1996. A year after the crisis hit, much of the gains has been eroded.

Exacerbating the problem was the drought brought by El Niño and later on the typhoons associated with La Niña. Both wreaked havoc on the agricultural sector and consequently on the poorer segments of the population.

• This study is aimed at assessing the social consequences of the crisis, with the end in view of contributing to the development of appropriate policy responses and reforms towards the strengthening of the social protection systems on a more sustained basis.

The study analyzes the nature and extent of the social impact of the crisis, identifies the specific groups adversely affected by the crisis, looks into institutional responses and household coping mechanisms, and determines areas where international organizations like the ADB can make useful contributions.

• Unlike previous studies of the same nature which had to base their analysis on very limited data, this study makes use of a rich set of information coming primarily from special data gathered for the specific purposes of the study and from regular and official statistics which were available only very recently. The former consists of primary data obtained through the participatory assessment approach involving the use of focused group discussions (FGDs), a key informant survey, and a household survey. The data was collected in January 1999 which is deemed appropriate from the point of view of being able to more or less capture the full impact of the crisis.

Economic Situation Prior to the Financial Crisis

• In the three years preceding the crisis, the Philippines enjoyed stronger economic growth compared to its sluggish pace in the early 90’s. It also experienced higher incomes and employment, stable prices, and favorable balance of payments and fiscal position. This was basically a result of the various policy reforms instituted in 19911996 which, among others, addressed infrastructure bottlenecks including the power supply situation, and stimulated investments and economic activity especially in deregulated and liberalized sectors.

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• While the performance of the economy was creditable when matched with historical trends, it lagged behind its neighbors (i.e., Thailand, Indonesia, China, Malaysia and Singapore) which had been growing at almost neck-breaking pace since the early 90’s. In spite of the growth experienced in 1994-1997, the country’s per capita GNP in dollar terms has not yet recovered to match its peak level in 1981. Economic growth was not enough to get back to historical highs in per capita GNP largely because of the roller coaster pattern of growth that the country has undergone since the late seventies as well as the consistently high population growth rate.

• As in other countries in the region, the country enjoyed substantial inflow of foreign capital especially portfolio investments in 1995-1996. This resulted in the strengthening of the peso which occurred in spite of the large trade deficit. The large proportion of portfolio investments to total foreign investments, the stronger peso combined with a large trade and current account deficit, and the deterioration of the BOP position in early 1997 made the economy vulnerable to speculative attacks on its currency. However, as later confirmed by the country’s experience after the start of the crisis, the various policy reforms instituted earlier, especially those that resulted in the strengthening of the banking system, made the country relatively more resilient to the impact of the crisis compared to some countries in the region.

Social and Human Development Situation Prior to the Crisis

• As the country experienced economic improvements during the few years prior to the crisis, the country posted positive trends in some key human development indicators.

(Reyes and Del Valle, 1998). This is expected to have stemmed from improved incomes and employment and from higher government spending on the social service sectors during the mid 1990s.

• Compared to 1986, the period 1994-1996 saw a marked improvement in the general health condition of the population. Available indicators show an increase in the average life expectancy, decline in malnutrition, and a reduction in crude death rate and in infant mortality rate. Similarly, poverty incidence dropped over the period 1986-1997. In spite of this improvement, however, the magnitude of poor people continued to swell.

• Despite the gains, the Philippines fared unfavorably compared to the other five ASEAN countries in terms of per capita incomes, unemployment, and poverty incidence. In terms of human development, it also fared poorly specifically in terms of life expectancy, low birth weight infants, crude death rate, infant mortality, employment, and access to sanitary toilet facilities. In terms of overall ranking for selected human development indicators, the country ranked fourth among the five ASEAN countries, better only compared to Indonesia.

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Economic Impact of the Crisis

• The most immediate impact of the financial crisis was manifested in the sudden outflow of substantial amounts of foreign capital which put a heavy strain on the country’s dollar reserves, thus resulting in the steep drop in the value of the peso (more than 62% within seven months after the crisis struck). To ease the pressure on the exchange rate, interest rates were increased by up to about seven percentage points at their peak level.

• Only a slight deceleration in GDP growth was felt in the first six months after the start of the crisis, with agriculture registering a flat growth and the industrial and services sectors showing some signs of weakening. In 1998, however, the economy contracted especially in the second quarter when the drought was most intense and in the fourth quarter when two strong typhoons hit the country. While the economic contraction is more due to the weather disturbances rather than the financial crisis, the marked decline in manufacturing and construction output during the period indicated that the adverse impact of the crisis had already been more deeply felt.

• Inflation slightly accelerated in the first few months after the crisis, with pressures coming mainly from services and housing and with food prices being somewhat stable. However, when agricultural output dropped drastically in the second quarter of 1998, the increase in food prices accelerated, bringing the overall inflation to doubledigit levels.

With the large depreciation of the peso, the balance of trade improved although occurring with some lag. In the six months immediately following the onset of the crisis, imports continued to outpace exports and the trade gap continued to widen. In 1998, imports dropped dramatically while exports continued to expand. By the second half of 1998, the trade balance turned into a surplus, drastically reducing the trade gap for the whole year. This, together with the availment of foreign borrowings contributed to an improved BOP position in 1998.

Fiscal Impact of the Crisis

• The financial crisis shaved off a substantial amount from expected government revenues which left the government with no choice but to cut back on its spending. In spite of the latter, the economy faced a bigger budget deficit by end 1998. The reduced spending meant a curtailment in the delivery of economic and social services although efforts were made to shield the latter from deeper budget cuts.

• In view of the revenue drop which was primarily caused by the dramatic shortfall in import duties, the government imposed a 25% reserve on total maintenance and operating appropriations of all national government agencies in February 1998. At the same time, it imposed a 10% reserve on the LGUs’ share in internal revenue allocation (IRA).

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• Most adversely affected by the austerity measures were the economic services sectors and national defense which suffered absolute budget cuts. On the other hand, the social services sectors and general public services were relatively protected, as the reserves on the social sectors were selectively lifted during the year. Still, real per capita spending on the social services sectors went down in 1998. Among the social sectors, most adversely affected were health, education, and housing/community services.

• With the government’s fiscal difficulties continuing in 1999, aggregate national government expenditures net of debt service based on the 1999 General Appropriations Act (GAA) will remain tight. However, expenditures on economic service sectors will somewhat recover.

• The national government’s austere spending in response to the crisis was mirrored at the local level as the latter encountered similar revenue difficulties. Over and above the reduction in their IRA shares, many LGUs registered a decline in locally generated revenues. In response, many LGUs imposed an across-the-board 25%-30% cut on non-personnel recurrent expenditures.

• LGU expenditures on economic services and other purposes were most severely affected by the fiscal crunch. As in the national level, the social sectors were accorded some degree of protection. Nevertheless, deterioration was noted as in the sample of LGUs surveyed, 11 out of 18 had lower per capita expenditures for social services.

Also following the pattern at the national level, the health sector seems to have suffered the most from the tight LGU budgets.

Social Impact of the Crisis

• The financial crisis had an adverse impact on the employment situation which was exacerbated by the El Niño. Total employment in 1998 grew at a slower pace and was not sufficient to accommodate the faster growth in the labor force. Thus, both the unemployment and underemployment rates went up during the year. Most hurt were the construction, manufacturing, and mining and quarrying sectors. Agriculture also suffered due more to the drought rather than the crisis.

This trend is supported by the FGD results which, while showing no massive lay-off, indicated significant loss of gainful employment. The more badly hit groups include urban poor and fishing communities. Many farmers and fisherfolks were forced to abandon their jobs for more viable sources of livelihood. By age group, the older workers, presumably the more skilled, were better able to hold onto their jobs.

DOLE’s survey of firms indicate that more firms either closed or retrenched in 1998 due to economic reasons. The number of firms which closed or retrenched in 1998 were double those in 1997. In wholesale and retail trade, financing, insurance, and real estate, the figures for 1998 are triple the figures in 1997.

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• The FGDs and the household survey show that many individuals (30% of respondents in the household survey) experienced lower incomes. The proportion of persons experiencing income declines was much higher for upland communities and sustenance communities. The middle income communities were less adversely affected. Among the major reasons cited for the decline in incomes were poor harvest due to bad weather, lower product prices, and reduced number of earning family members especially among middle-income households.

In spite of the crisis, however, a number of households (17% of respondents) reported higher income, due mainly to job promotion, increased number of earning family members, better product prices, and new or additional work. Increased financial support from relatives was also cited as one of the main reasons for higher incomes reported in urban poor communities. This indicates the strengthening of the family support system during the crisis.

Among workers, those employed overseas benefited the most from the crisis because of the higher peso value of their dollar earnings. This is in spite of the decline in dollar earnings and remittances in 1997 and in 1998.

• While not all individuals experienced lower nominal incomes, price increases affected everyone, indicating declines in real incomes. Inflation rate in 1998 went up to 9%, from 5% in 1997 as a result of the peso depreciation and the food supply bottlenecks caused by the El Niño and La Niña. Food prices alone rose by 6.4%.

FGD respondents felt that the sharp increases in prices were not matched by corresponding increases in wages and earnings, thus, implying weakened purchasing power and a decrease in access to basic services.

• The household survey indicates that the proportion of families who rated themselves poor rose from 40% in 1997 to 43% in 1999. The highest self-rated poverty seems to be evident among fishing and upland communities and among households in urban poor communities. The Social Weather Station surveys also indicate an upward trend in self-rated poverty between 1997 and 1998. The increase in poverty incidence is by itself not very large but is still a cause for concern because the poverty incidence is already high to begin with.

It should also be noted that while some households experienced lower incomes, a significant number of the household respondents (38%) also indicated that their wellbeing improved in spite of the crisis, and another big portion (30%) were unaffected.

These consist mostly of families in the middle income communities.

• Lower enrolment rates and higher drop out rates are the primary effects of the crisis on the education sector as indicated by the FGDs. This seems to be most especially true in depressed communities such as the urban poor, sustenance farming, and upland and fishing communities. Among the specific reasons given are financial difficulties, inability to cope with higher tuition fees and school expenses and higher out-of-pocket costs (e.g., transportation, school projects), and the need to give priority to more essential items such as food. The increase in drop out incidence was more v

greatly felt in public secondary schools and did not seem to be very large in elementary and private secondary schools.

Based on government’s administrative reports, there was a slight growth in enrolment in public elementary schools between school year 1997-98 to 1998-99, but a considerable decline for the secondary level. There was, however, a decline in enrolment in Grade 1 and a slowdown in the growth of enrolment in the first year level. This indicates that families have postponed the enrolment of new entrants both to elementary and secondary level. Meanwhile, enrolment in private schools showed significant drops. It is speculated that a shift occurred in enrolment from the private to public schools at the elementary level.

• The more significant and evident impact of the crisis on the health sector is the reduced availability of medicine supplies and vaccines and other health services such as immunization. This has been strongly felt by the survey respondents and is consistent with the drop in government health expenditures both at the national and local levels. The skipping of meals is not prevalent and does not appear to have resulted in higher incidence of malnutrition.

• The financial crisis also affected the especially disadvantaged groups. In the case of farming communities, the severity of the El Niño aggravated the situation. Among farming and fishing communities, the impact of the crisis was experienced through higher input prices. Fisherfolks faced better market price for their produce but it was not enough to offset cost increases. The situation is worse for farmers who could not sell their produce at higher prices as they were usually at the mercy of traders and/ or landowners. On the children and youth, the adverse effect of the crisis was felt through the coping mechanisms adopted by poor families which, in general, have compromised the health, education and overall development of these young individuals. In the case of women, they took the added burden of stretching the household budget, looking for additional income-earning opportunities, and finding of credit sources or money to pay loans.

• The country’s social fabric seems to have been left relatively unscathed by the financial crisis. In spite of the economic and financial difficulties faced by individuals and families, communities in general have remained peaceful. In a few communities though (particularly those among the urban poor and fishing villages), an increase in incidence of drug-related problems and criminality has been reported.

Responses to the Crisis and Coping Mechanisms

• Focusing on the social-related responses to the crisis and coping mechanisms, the government implemented certain measures to establish social safety nets and assist displaced workers. The business sector, which was doubly hit by the crisis through weaker demand and higher costs, resorted to cost-cutting measures such as freezing of salary increases and cutting down of work hours. Among households, the main coping mechanisms employed were the search for additional income-earning opportunities and adjustment in the household budget. vi

• In line with its objective of establishing social safety nets to cushion the poor from economic adversities, the government carried out various measures consisting of food and health care assistance to vulnerable groups affected by the crisis as well as the drought. These include the setting up of sari-sari stores that would sell basic food commodities at lower prices, continuation of the program on the comprehensive and integrated delivery of social services (CIDSS) to address the unmet needs of the poor, selling of rice at discounted prices by the National Food Authority rolling stores in targeted poor municipalities, and other forms of emergency assistance.

The government also provided assistance to displaced workers consisting mainly of the following: rural works projects specifically in Mindanao and in the CARAGA region; an emergency loan package for displaced sugar workers; strengthening of job facilitation services; loan programs and measures to ease repayment of loans by SSS members; and training and retraining intervention programs through the Technical Education and Skills Development Authority (TESDA).

• Based on the Survey of Philippine Industry and the Asian Financial Crisis undertaken in late 1998 (Lamberte and Yap, 1999), many manufacturing firms resorted to cutting down of work hours or days to minimize job losses while some implemented costcutting measures like freezing of salary increases, imposing forced vacation, enforcing compressed work week, and for a small number of firms, implementing salary cuts. In the same vein, the FGDs cited other cost cutting measures such as job rotation, longer working hours without additional pay, hiring of workers on a contractual basis, and employment of women at below minimum wage.

• The FGD reports indicate that many of those who lost their jobs tried to seek some part-time work, mainly in retail trade and doing odd jobs. Women in households where the males were displaced tried to augment the household income by seeking jobs or undertaking self-employment mechanisms such as direct-selling and setting up sari-sari stores or carinderia. In certain cases, children were also made to work mostly as laborers (for the men), or as domestic helpers (for the women).

• Among households, one common coping mechanism is adjusting the household budget, giving priority to more essential items like food and allotting more for education, medical/health, transportation and housing expenses to keep up with rising costs in these areas. Needs for clothing and leisure were sacrificed. Some changes in food consumption patterns were also made by doing away with non-essentials, having only one viand per meal, eliminating snacks, sleeping longer hours, and resorting to cheaper food substitutes.

To meet their financial needs, majority of the households surveyed resorted to borrowing or availing of credit, mostly from the informal sectors or from relatives and friends. When credit was not accessible or available, some households resorted to selling assets to raise cash.

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Assessment of Existing Monitoring Systems

• Most of the studies done on the impact of the crisis had to rely on very limited information because the existing monitoring systems especially for assessing social impact is very much inadequate in terms of timeliness, identifying affected sectors, and providing a full picture of what happened to the affected sectors. Social indicators, unlike economic indicators, are generally fewer and infrequently collected.

Some data are available at the local level but it takes a long time before they go up to the national level. On the other hand, some indicators are too aggregated to provide useful information for targeted interventions. These problems have made the rendering of appropriate and timely response to the crisis very difficult.

•

At the national level, there is no single monitoring system that tracks the country’s performance vis-à-vis the different aspects of human development. There are different data sources that can provide indicators on the different dimensions of welfare but a more comprehensive and integrated assessment and analysis is done only about every three years when the national development plan is either formulated or updated.

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At the community level, there recently had been various efforts to come up with community-based monitoring systems. These are integrated with various projects including the following: Micro-Impacts of Macroeconomic Adjustment Policy (MIMAP) project; Comprehensive and Integrated Delivery of Social Services (CIDSS) project; and the Minimum Basic Needs (MBN) project of the former Presidential Commission to Fight Poverty (PCFP), now merged with the newly created National Anti-Poverty Commission (NAPC). Except for CIDSS, the monitoring systems which are proposed or undertaken under these projects, however, are not operative on a regular basis.

• In view of the importance of providing timely and adequate information on the social impact of a crisis in providing immediate and effective response, it is important that an appropriate monitoring system be put in place.

Conclusions and Recommendations

• It is clear that the financial and economic crisis, together with the El Niño and La Niña, has affected the vulnerable groups through reduced employment and higher prices which resulted in lower real incomes. This in turn forced affected households to look for other income opportunities and to make adjustments in their spending and consumption patterns. Because of financial difficulties faced by households, their need for public social services increased. Unfortunately, because of the fiscal crunch, the delivery of social services especially in health suffered.

• On the whole, the social impact of the crisis in the Philippines does not appear to be very serious by itself and relative to the crisis-related experiences in Indonesia and viii

Thailand as initially reported. The policy reforms instituted in the years prior to the crisis seems to have been timely and have contributed to the greater resiliency of the economy to the crisis. Compared to the impact of the debt crisis in the early 80’s, the impact of the present crisis also seems much more manageable.

• This, however, does not offer much of a comfort considering that prior to the crisis, the Philippines was way behind other ASEAN countries in both economic and human development aspects . The country’s welfare situation was already very serious to begin with and any further slippage, no matter how small, is not acceptable.

• On the fiscal side, it is unfortunate that the provision of basic social services is curtailed when it is most needed. Worse, access to the services by persons or families who need it most is not assured by the present social service delivery system. This problem is reinforced by the absence of a strong monitoring system that would identify the individuals and groups that should be targeted.

• There are two ways of addressing this problem. First, by making available the necessary resources to reach the identified families or individuals when the situation calls for it. Second, by ensuring a more effective allocation and utilization of resources through more focused targeting mechanisms and more effective projects with immediate or significant impacts.

• On the first point, the analysis indicates that although the social service sectors were protected relative to other sectors from the fiscal crunch, the shortfall in government revenues is of such magnitude as to effectively reduce the budget cover for and, consequently, the coverage of basic social services. Undoubtedly, there is a need for additional sources of deficit finance if this problem is to be addressed. Domestic borrowing, however, carries the risk of raising local interest rates which may then stifle nascent recovery efforts. Thus, there is a need for government to look at external sources of finance. In this light, external assistance from donor agencies in the form of budget support is called for.

A number of donor agencies are in the process of providing budget support to the government. Given this perspective, such budget support may be made conditional on government commitment: (1) to increase resources allotted to the social service sectors, and (2) to rationalize the allocation of resources within the social service sectors.

• On the second point, a targeting mechanism that is more community-based and brought down further to the barangay level should be pursued. The barangay is deemed to be the most appropriate focal point for identifying beneficiaries, determining their needs, and delivering the required services. The minimum basic needs (MBN) approach which promotes participatory planning at the community level can be strengthened and supported.

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• To support a community-based targeting mechanism that will provide timely and adequate response to a crisis, a strong social monitoring system has to be also established and maintained. The following are the recommendations towards the establishment of such a system: 1) Obtain and integrate existing information from various sources (administrative reports, official statistics, censuses and surveys) at the national and community level; 2) Create appropriate data banks at each geopolitical level; 3) Strengthen and expand the MBN community-based information system; 4) Integrate the community-based monitoring system with the local planning process; and 5) Designate a focal agency to be responsible for the coordination and maintenance of the social monitoring system and for the reporting of performance based on the results under the monitoring system.

• In addition to ensuring the availability of resources and adopting a community-based targeting mechanism, the specific issues in various areas of concern have to be addressed. The specific recommendations along this line are as follows: 1) Access to Basic Commodities. Support programs that enhance access to basic commodities by making such commodities available in targeted areas at lower than market price. This may mean greater support for programs like the ERAP stores and the rice subsidy program.

2) Employment. Undertake pump-priming programs that will create employment opportunities. The use of more labor- intensive techniques in infrastructure projects and the adoption of the Community and Employment Development Program is also recommended As a medium and long-term strategy, address structural problems that persistently cause high unemployment. This should be tied to the agriculture modernization program and to efforts that will address the weaknesses in the manufacturing sector. Infrastructure support to agriculture should be pursued.

Meanwhile, educational reforms should be carried out to ensure that skills are matched with market requirements.

3) Credit. Promote credit programs that match the collateral base and cash flow of borrowers. Grameen-type programs in providing the poor access to credit should be encouraged. The NGOs or cooperatives can be tapped for the implementation of these credit programs.

4) Health, Nutrition and Population. To address structural issues, focus on the provision of primary and public health care services rather than of curative care. At the same time, pursue the social insurance-based financing for access to curative care.

For women, provide more consistent support for family planning programs and more human capital investment opportunities. Increase funding for contraceptive supplies to arrest the decline in contraceptive prevalence.

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As a short-term response, provide special support for the immunization program. Well- targeted feeding programs should also be expanded.

5) Education.

To address the structural issues, rationalize government investments in tertiary education. In basic education, pursue cost recovery schemes in areas such as textbooks. Efforts at choosing more cost-effective options as opposed to that of providing “elementary school in each barangay and a high school in every municipality� should be made. Providing bus service and dormitory housing for students in far-flung areas should be considered.

Short-term measures should include the redesigning of the Government Assistance to Students and Teachers in Private Education (GASTPE) to allow for increasing the support value of the subsidy under the program. Including out-of-pocket costs on top of the usual coverage should be considered.

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I.

INTRODUCTION

Almost two years has passed since the start of the financial crisis that hit Asia, including the Philippines, in July 1997. While the currency situation has stabilized, the effects of the financial turmoil continue to linger. The crisis, together with the El Niùo and La Niùa, caused economic contraction, increased unemployment, and higher prices. These had adverse social consequences and forced many affected families and individuals to make adjustments especially in their consumption and spending patterns. The government, faced with huge revenue shortfalls, adopted austere measures which caused reductions in its spending on a number of economic and social services. While this helped in minimizing the deficit, it aggravated the situation as it tended to weaken rather than strengthen the government’s capability to provide assistance to those adversely affected by the crisis.

This study aims to take a closer look at the social impact of the regional financial and economic crisis in the Philippines with the end in view of assisting in devising policy responses and identifying reforms that would strengthen the social protection system on a more sustained basis. Unlike similar studies which were done earlier, this study benefits from being able to use official statistics that were made available only recently and from supplementary data gathered specifically for the purposes of this study.

This chapter discusses the specific objectives of this study, the framework of analysis used, the background on the causes of the crisis, the major findings of previous studies done, and the sources of the data utilized for this study.

In the second chapter, the economic and human development situation prior to the crisis is discussed. This, together with the economic impact of the crisis presented in Chapter III, is aimed at setting the proper perspective for discussing both the fiscal and the social impacts of the crisis, which are tackled in Chapters IV and V, respectively.

1. Specific Objectives This study is undertaken with the following specific objectives in mind: 1) Examine the transmission of adverse social impacts from the financial and economic crisis, and analyze the nature and extent of these impacts; 2) Identify the various groups affected by the economic crisis and assess the differential impacts on them at the micro-level; 3) Review the various responses of the government, private sector, and other institutions, as well as the household responses or coping mechanisms to the crisis; 4) Assess the existing monitoring systems for tracking social impact of the crisis; and 1

5) Determine areas where the Asian Development Bank (ADB) and other international organizations can make useful contribution.

2. Framework of Analysis1 There are four main channels through which the financial and broader economic crisis may have an adverse social impact. The first channel is through the effects of the crisis on employment, earnings, and income of households. Unemployment may rise not only because of increased number of business failures but also due to job losses in businesses experiencing substantially reduced sales.

In an effort to maintain employment, and in some possible cases with the consent of employees and labor unions, many businesses may allow real wages to decline in the presence of inflation and additionally reduce employee benefits or shorten working hours. Informal sector workers may also experience reduction in income due to declining sales and rising prices of inputs with high import content (e.g., fuel).

The second channel is through the effect of the crisis on consumer prices. Prices of imported goods or goods with a high import content (e.g., pharmaceuticals, and fuel) may have increased dramatically. Prices of tradables, including notably rice and other basic foods, may have also increased (although the extent of the price changes may vary somewhat from country to country depending on the extent of government intervention).

The third channel by which the economic and financial crisis may have adverse social impact is through the government budget. Tax revenue may fall due to the economic slowdown while government expenditure may be reduced in order to provide additional funds to pay for the restructuring of domestic financial institutions and repay foreign debt. Although efforts may be made in some cases to maintain previous levels of government expenditure on key social services such as health and education, the availability of such services to the poor may be adversely affected by inflation and by increased demand from persons who previously used private services.

A fourth channel is through the crisis' effect in reducing the demand for migrant labor throughout the region. This may lead to the return of many overseas migrants and may prevent others from taking advantage of an important, traditionally available outlet for coping with economic adversity.

Although the impact of the crisis may adversely affect most population groups, its severity may vary from group to group.

Households may use a variety of ways to cope with the primary impact of the crisis, including adjusting their consumption and savings behavior and labor supply to the changes in relative prices, employment opportunities, wages and wealth (including adjusting their utilization of health and schooling services), migrating to other domestic or foreign locations in order to access different prices and wages and different 1

This section is based on the “Social Impact of the Financial Crisis in Asia: Economic Framework� Asian Development Bank, November 1998.

2

employment opportunities, and adjusting their utilization of and contributions to the social capital stock. Other institutions may have also responded to the crisis, including communities, businesses and labor unions governments, regional organizations, and international donors. Many of these responses (particularly the coping mechanism of households) may have additional secondary or indirect adverse social impacts.

3. Data Sources and Methodology A participatory assessment approach was the primary tool utilized in determining the social impact of the financial and economic crisis specifically on vulnerable groups and in identifying the coping mechanisms adopted by households in response to the crisis.

Focus group discussions (FGDs) were conducted in January 1999. This timing is thought to be appropriate from the point of view of being able to get a more complete picture of the impact of the crisis in the Philippines. The FGD covered 57 communities (barangays or villages) all over the country representing fishing, urban poor, middle income/wage earner, and farming (upland, sustenance, and commercial).

In addition, a key informant survey and a household survey were conducted to provide supplementary data. The key informant survey covered 31 out of the 57 FGD communities and tried to elicit views from community-based leaders regarding the impact of the crisis in the community. The key informants included the barangay chairman, the health worker, nutrition scholar, principal or head teacher, and social worker. Additional respondents were also interviewed in the municipalities where these barangays are situated and these included the municipal accountant, budget officer, health officer and social welfare officer.

The household survey consisted of 430 households in the same 31 communities.

Sample households were selected based on spatial and sectoral dimensions. The spatial grouping considered four broad divisions: Mega Manila, Luzon, Visayas, and Mindanao while the sectoral divisions were based on the dominant economic characteristics of the community.

Secondary data were also obtained from the following: (1) administrative reports of various government agencies; (2) budget data of national and local governments; and (3) surveys done by the National Statistics Office (NSO). Administrative reports of the Department of Education, Culture and Sports (DECS) and Department of Health (DOH) and Department of Social Welfare and Development (DSWD) were utilized. Budget and expenditure data from the Department of Budget and Management, Commission on Audit, and selected local government units provided the data on national and local government spending. The NSO data include those obtained from the quarterly Labor Force Surveys, triennial Family Income and Expenditures Surveys, and the 1998 Annual Poverty Indicators Survey.

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4. Background on the Origin and Causes of the Crisis The Asian financial crisis that struck in July 1997 was triggered by speculative attacks on the Thai baht. International currency speculators withdrew their funds from the country, exerting excessive pressure on the country’s foreign exchange reserves. The Thai Central Bank at first tried to protect the baht but was unsuccessful. After attacking the Thai baht, international currency speculators triggered several rounds of currency depreciation in other countries including the Philippines, Indonesia, Malaysia, Singapore, and South Korea. (See Table I.1).

There are three main reasons cited for the speculative attack on the Thai baht: (1) its being overvalued as reflected mainly in the growing trade and current account deficits, (2) a rapid increase in the country’s debt servicing requirements relative to its foreign exchange earnings owing to the accumulation of a large foreign debt, and (3) unproductive investments in non-tradable services and in real estate involving businessmen with good political connections (ADB, 1998).

The underlying factors that made the Thai baht vulnerable to speculative attacks were also present in other countries hit by the crisis although at varying degrees of importance. In the case of the Philippines, the following factors contributed to the vulnerability of the peso: (1) Overvaluation of the Peso.

In spite of a large current account deficit, which amounted to around 4.5 % of GNP, the peso appreciated in 1994 and 1995 and depreciated only slightly in 1996. The large inflow of foreign capital, which was encouraged by the liberalization of foreign exchange and investment, allowed the peso to strengthen in spite of large trade and current account deficits.

(2) Increase in portfolio investments.

With the liberalization of foreign exchange and investments in the early 1990’s, foreign investment inflows surged in the mid-1990’s. Significant increases in direct foreign investments were realized in 1992-1994 while portfolio investments rose from less than $100 million a year in early 1990’s to $2.2 billion by 1996.

Direct foreign investments are longer-term in nature and should be relatively more stable as they could not be easily withdrawn. However, portfolio investments or aptly referred to as “hot money” can easily flow in and out of the country almost instantaneously and can therefore cause instability in the foreign exchange market.

By 1996, net portfolio investments accounted for 62% of total net foreign investment in the country. As early as the first half of 1997, this “hot money” already started flowing out in significant magnitudes thus causing a negative net

4

portfolio investment inflows during the period. Direct foreign investment continued to come in in the first semester but substantially dropped in the second half of the year although remaining positive. (See Table I.2).

Just like in other Asian countries, the Philippines resorted to higher foreign borrowings in the mid-1990’s. In terms of magnitude, however, the Philippines was relatively more prudent in its foreign borrowings compared to the other Asian countries.

Its external debt in 1996 was only 33.4% higher than its debt five years earlier while those of the other East Asian countries have more than doubled, except for Indonesia which actually declined. In the case of Indonesia, however, its debt has increased substantially relative to its GDP (see Table I.3).

The Philippines also experienced a boom in the property market during the mid1990’s which made bank lending to this sector increase substantially. However, unlike in other Asian countries, the exposure of the Philippine-banking sector to the property market was less compared to its neighboring countries like Thailand. The Philippines, to a certain extent, learned its lesson from the Thai experience where the bursting of the bubble occurred earlier and the Philippines had the benefit of obtaining warning signals that enabled it to regulate the further exposure of Philippine banks to the sector.

While the Philippines had an overvalued currency that made it vulnerable to speculative attacks, its foreign borrowings and banking sector’s exposure to the property sector were more prudent. Moreover, it was experiencing strong macroeconomic fundamentals because of the policy reforms that it had earlier implemented. However, the country did not get spared from the crisis largely because of the “herd mentality” of both the portfolio investors and foreign private lenders which “looked at the entire ASEAN region as if it were homogenous even if there were differences in economic fundamentals from country to country” (Lim, 1998).

5. Review of Previous Studies Done There had been several studies done to assess the various effects of the crisis in the Philippines. Among these, there are two which specifically focus on the social impact of the crisis. The first study was undertaken by the World Bank (East Asia Pacific Regional Office) in February 1998 and the second was done by Joseph Lim under the auspices of the United Nations Development Programme in June 1998. Having been done at a relatively short period of time after the crisis, the World Bank study had to rely basically on foreseen rather than actual trends while the UNDP study employed various means of working with secondary data including regression analysis.

The World Bank study assessed the socio-economic impact of the crisis on wage and employment, credit market, health and education. It was found that at the time of the study, the social impacts of the crisis have not been conspicuous and dramatic.

Nevertheless, five foreseen trends were identified involving mainly the expected impact of the devaluation, namely: 1) Higher inflation which will result in lower real incomes; 2) Higher interest rates which renders the cost of doing business difficult; 3) Lower government budgets allocated for health and education which could mean reduced

5

services delivered; 4) Tightness in credit; and 5) potential and imminent threat on social cohesion.

To safeguard the poor from lower real incomes due to higher prices, the World Bank study recommended direct transfers in cash (welfare payments and public works) and in kind (commodity subsidies). To alleviate the impending unemployment problems brought about by the crisis, the study proposed employment generation schemes. It was also recommended that health and education be protected from budgetary cuts, and over the long run, the allocation for these sectors should in fact be increased.

As in the World Bank study, Lim’s study found that higher unemployment and inflation are the short run effects of the crisis. These translate to decreased real incomes, decline in social and human development indicators, increases in the number and incidence of poverty, and deterioration in income distribution. The medium-term impacts of the crisis are linked with the imminent effects of the 25% mandatory reserve on the provision of social services. The long-run effects are considered to be the lower health and education status of the population. These conclusions were derived basically from Lim’s regressions of human and social indicators on economic factors. Lim’s major breakthrough in coming up with the likely impact of the crisis is the sociological perspective he lent on studying the overall social milieu. He warned of the greater pressure to be placed on the extended family system and overseas migration as these two might be used as safety nets for increased poverty resulting from the crisis.

To address the impacts of the financial turmoil, Lim made the following recommendations for the short run: 1) International and regional efforts to address issues on exchange rates and capital flows; 2) Protecting basic social services, human development programs and key infrastructure projects from fiscal cutbacks; and 3) Prioritizing and intensifying poverty alleviation programs. The medium and long-run strategies he proposed are: 1) Agricultural and rural development to strengthen ruralurban and regional linkages; 2) Greater emphasis on human capital formation; 3) Higher investment in science and technology and research and development to raise productivity and hence, real wages; and 4) More balanced infrastructure spending.

In the absence of data to determine the impact of the crisis on social outcomes, Reyes (1998) used the MIMAP models to simulate the likely impact of the crisis on education, health and nutrition. Reyes finds that due to the combined effects of the crisis and El Niño, average incomes of all deciles will decrease and the GINI ratio will go up.

Moreover, the simulations indicate that enrolment will tend to decline, nutrient availability will decrease and there will be greater demand for public health care facilities. The study highlights the need for measures to bring back the drop-outs into the educational system. Targeted food assistance programs will help stem the rise in malnutrition. The study calls upon the government to prioritize the provision of basic health and education services since the poor are expected to rely more on publiclyprovided services in times of crisis.

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II.

ECONOMIC AND HUMAN DEVELOPMENT SITUATION PRIOR TO THE CRISIS

To set the proper perspective for assessing the economic and social impact of the financial crisis in the Philippines, it is necessary to review the economic and human development situation during the decade preceding the crisis.

1. Economic Situation Philippine economic growth has followed a roller-coaster pattern in the past years or what many economists call a boom-bust cycle. A financial crisis of a different nature hit the economy in 1983-84 which caused dramatic economic contraction in 1984 and 1985. Then, the years 1986-1989 saw the Philippine economy recovering from the crisis, with the restoration of democracy and the institution of policy reforms (e.g., dismantling of monopolies) resulting in renewed investor confidence, thus, stimulating economic activity. In 1989-1991, a series of coup attempts on the Aquino administration stifled investment growth while natural disasters like the Mt. Pinatubo eruption adversely affected agricultural production and the business sector. Moreover, the power shortages which were at its worst in 1992 and other infrastructure constraints curtailed economic expansion. From 1991-1993, the economy grew at a snail’s pace (Figure II.1).

Meanwhile, new economic policy reforms were instituted in 1991-1996. These reforms addressed infrastructure bottlenecks particularly in power supply and stimulated investments and economic activity in the deregulated industries. From a sluggish pace in 1991-1993, GDP growth accelerated in 1994 and 1995 and reached 5.8% in 1996. Thus, from 1994-1996, both the industrial and the services sectors exhibited renewed growth.

In spite of its good showing in 1994-1996, however, the Philippine economy was a laggard compared to its neighboring countries most of which grew within a 7-12% range (Table II.1). For this reason, the Philippines was considered to be a “basket case” in a region where most of the countries were already considered as economic tigers.

As Philippine growth followed a roller-coaster pattern, so did the country’s per capita GNP. Because of the ups and downs experienced in the economy over the past one and a half decades, long-term real per capita GNP has been stagnant, with its 1997 level not very far from where it was fifteen years ago (Figure II.2).

During the few years prior to the financial crisis, the Philippines has been enjoying single-digit inflation of around 8.5% which in the first half of 1997 even went down to 4.6%. This is in contrast to that in 1989-1991 when inflation reached doubledigit levels as the country experienced a substantial increase in the peso-dollar rate. In 1994-1996, stable food prices generally prevailed. The greater competition spawned by the policy reforms encouraged price stability during this period. Moreover, the peso appreciated vis-à-vis the dollar while interest rates were kept at relatively manageable levels (Table II.2).

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During the three years prior to the crisis, the Philippine economy was not only enjoying a favorable economic growth and relatively stable prices but also a favorable balance of payments and fiscal position. From deficits in the fiscal position during the whole of the 1980’s and early 1990’s until 1993, surpluses were posted in 1994-1997 (Figure II.3).

Likewise, the balance of payments position reflected surpluses during the same period except in the first half of 1997 when the BOP turned into a deficit. Meanwhile, the country’s gross international reserves was kept at a healthy level, enough to cover about three months’ worth of import requirements. The country’s external debt grew at a modest pace, thus making debt-servicing requirements manageable (Table II.3).

To summarize, the macroeconomic indicators show that in the few years prior to the financial crisis, the economy’s health was in relatively good condition as it enjoyed strong macroeconomic fundamentals. Nevertheless, there were signs of increasing vulnerability as the BOP position started to deteriorate in early 1997. The strengthening of the peso in 1994-1996 despite a wide trade gap, and the increasing flows of portfolio investments made the economy vulnerable to potential shocks in the global capital market.

Meanwhile, as the crisis started to be felt, the economy faced other developments that impinged on its performance. At about the same time that the financial crisis hit, the Philippines was affected by the dry spell brought about by the El Niño phenomenon. The adverse effects of the El Niño started to be felt in the late 1997 but worsened in the second quarter of 1998.

2. Human Development Situation Available data show that the Philippines experienced improvements in some key human development indicators during the decade prior to the crisis (Reyes and Del Valle, 1998).2 This is expected to have resulted from improved incomes and employment and from higher government spending on the social sectors during the mid 1990’s.

Compared to 1986, the period 1994-1996 saw a marked improvement in the general health condition of the population. Available indicators show an increase in the average life expectancy, decline in malnutrition, and a reduction in crude death rate and in infant mortality rate. From 1986 to 1995, life expectancy rose from an average of 63.4 years to 69.1 years. Malnutrition prevalence rates declined from 9.9% in 1992 to 8.4% in 1996 for underweight children. Meanwhile, the country’s crude death rate went down from 6 per 1,000 population in 1986 to 5 per 1,000 population in 1994. The infant mortality rate exhibited the same positive trend, declining from 63 to 47 per 1,000 live births for the decade 1986-1996.

2

This section draws heavily from the analysis and observations of Reyes and Del Valle in their paper on: Poverty Alleviation and Equity Promotion (1998).

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Consistent with the above-mentioned trends, the poverty incidence dropped over the period 1986-1997. In 1997, the poverty incidence reached 32.1%, down from 35.5% in 1994 and from 44.2% in 1985. Similarly, the subsistence incidence which measures the proportion of the population unable to meet their basic food requirements, otherwise known as the “core poor�, went down to 16.5% in 1997, from 21.8% in 1994 and 28.5% in 1985.

In spite of the improvement in the poverty incidence from 1986-1997, however, the magnitude of poor people continued to swell. This reflects the very slow pace of improvement in the poverty situation.

Despite the significant gains made over the past decade, the Philippines fared unfavorably compared to the other five ASEAN countries in terms of per capita incomes, employment, poverty incidence, and human development indicators. In the decade prior to the crisis, most countries in the region such as Thailand, Indonesia, and Malaysia have experienced much faster economic growth than the Philippines (Table II.1). In terms of per capita income, the country ranked as the second lowest, next only to Indonesia.

(Table II.4). In terms of unemployment, the Philippines had the highest rate in 1995, much higher than most countries in the region (Table II.5). The country also fares miserably in terms of poverty condition as the country with the next worse poverty incidence (i.e., Indonesia) has a rate that is already way below that of the Philippines (Table II.6).

In terms of human development, the Philippines also fared poorly compared to other ASEAN countries specifically in terms of life expectancy, low birth weight infants, crude death rate, infant mortality, employment, and access to sanitary toilet facilities (Tables II.7 and II.8). However, it ranked first in adult literacy, mean years of schooling, and growth of earnings per employee. In terms of overall ranking for selected indicators, the country ranked fourth among the five ASEAN countries, better only when compared to Indonesia.

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III.

ECONOMIC IMPACT OF THE FINANCIAL CRISIS IN THE PHILIPPINES

The Asian financial crisis was immediately transmitted to the Philippine economy through the large capital outflows which instantly created downward pressure on the peso as well as resulted in a deterioration of the balance of payments position. This was readily accompanied by the raising of domestic interest rates and the tightening of monetary policies which aimed to reduce speculative pressures. Initially, economic growth remained strong but eventually slackened after a semester, exacerbated by the illeffects of the El Niño and later on the La Niña. An improvement in the trade balance ensued, and later on in the improvement of the balance of payments position, on account of the dramatic contraction of imports. However, the latter resulted in shortfalls in government revenues, which put the fiscal position back in the red.

1. Exchange Rate The most immediate impact of the financial crisis was manifested in the sudden outflow of substantial amounts of foreign capital, which readily resulted in the substantial depreciation of the peso.

As the Thai baht gave way due to speculative attacks, international currency speculators turned to other countries in the region including the Philippines. These currency speculators withdrew their portfolio investments in the country while foreign private lenders and other investors held back. This resulted in substantial amounts of capital outflows. While the BSP initially tried to defend the peso by dipping into its foreign exchange reserves, the peso value gave in as the country’s reserves was not large enough to support such massive outflows.

From P26.40/$ in June 1997, the peso-dollar rate shot up to P27.70/$ in July, continuing to increase up to January 1998 (Figure III.1). In January 1998, the peso-dollar rate reached its peak level, moving to an average of P42.70/$ for the month, or 62.4% higher than the exchange rate just before the crisis. For the rest of 1998 and in the first quarter of 1999, the exchange rate showed greater stability although it continued to reflect the on-and -off jitters in the Asian currency market. Towards end-1998, the peso even strengthened as the regional currency market exhibited relative calmness and as the country’s reserves improved with the availment of new foreign borrowings.

2. Interest Rates From 1993-1996, the bellwether 91-day Treasury bill rate averaged 12.31%, coming from a high of 20.4%, the average for 1990-1992. In the first half of 1997, the 91-day Treasury bill reached a low of 10.5%.

As the crisis struck and hit the peso, the government raised interest rates to ease the pressure on the exchange rate. The 91-day Treasury bill rate went up to 12.2% in July and peaked at 19.1% in January 1998, the same period when the exchange rate 10

reached its highest level (Figure III.2). In the succeeding months, however, interest rates followed a downtrend as the peso-dollar rate stabilized. By end-1998, the 91-day Treasury bill rate has slid to 13.4%, closer to the levels before the financial crisis. This downtrend continued in early 1999.

Following the uptrend in the 91-day treasury bill rate, bank lending rates rose in July 1997 and in the months that followed, reaching more than 20% in the last quarter of the year and in early 1998. In February and March 1998, bank lending rates did not drop as much as the decline in the Treasury bill rate but went down more substantially in the succeeding months (Figure III.3).

3. Economic Growth In the first six months of the crisis, the economy registered a respectable growth, continuing the momentum that has been achieved in 1994-1996. Only a slight deceleration in GDP growth was felt in the second semester of 1997 with the agriculture sector registering a flat growth in the third quarter and the industrial and services sectors showing some signs of weakening in the fourth quarter. In particular, the construction sector, which continued to show strong growth in the third quarter of 1997, slowed down considerably in the fourth quarter of the year, an indication that the glut in the property market started to be felt (Table III.1).

In 1998, however, the economy contracted especially in the second and fourth quarter of the year. While this could have been more a result of the weather disturbances than the financial crisis, the marked decline in manufacturing and construction output indicated that the adverse impact of the crisis had already been more seriously felt especially as the business sector had been squeezed on two sides – higher cost of funds and a weaker consumer market.

Largely responsible for the economic contraction in 1998 was the agricultural sector which was adversely affected by the El Niùo in the second quarter and by typhoons which hit the country in October. The performance of the agriculture sector during the year was one of the worst in the history of the Philippines. For the whole year 1998, the country’s two leading crops, palay and corn, declined by 24.1% and 11.7 % respectively.

The sectors that appear to have been most hurt by the financial crisis were the construction and manufacturing industries, which were enjoying strong growth prior to the crisis. The construction sector benefited not only from the boom in the property market in the earlier years but also from the development of infrastructures. In 1998, the output of these two sectors declined, with the drop in construction being more pronounced. In manufacturing, most badly hit were the following subsectors: transport equipment, metal industries, nonmetallic minerals, rubber products, basic metals, petroleum products, textiles, and chemical products.

In a related development, a number of multinational companies have been reported to have closed or to have plans of closing in 1999 their manufacturing facilities 11

in the country due to what many describe as a “rationalization� of production units.

Among these companies are Colgate-Palmolive, Johnson and Johnson, Warner Lambert, Abbot Laboratories, Philips Electric and Lighting, and Van Melle. (Business World, Feb. 25, 1999). Some companies have cited as reason the overcapacity in Asia in the light of dwindling demand caused by the crisis.

On the demand side, most adversely hit by the crisis was investment spending.

While the completion of ongoing and planned investment activities continued to prop up investments in the second half of 1997, investment spending declined substantially in 1998. High interest rates and the difficulty of obtaining financing, combined with uncertainties in the economic environment discouraged investment activity. In the second half of 1998, the wait-and-see attitude of investors with regard to the newly installed administration seems to have added to the weakness in investment activity.

Exports of goods in real terms posted a substantial deceleration in 1998 while imports of goods registered a significant decline (Table III.2). However, total trade has been pulled down further by the dramatic drop in exports and imports of non-factor services. This is largely on account of the negative impact of the crisis on the travel and tourism industry as well as on miscellaneous services.

One of the significant developments in the recent years is the dramatic increase in the inward remittances of dollars by overseas Filipino workers (OFWs). From only $2.3 billion in 1993, personal income remittances from OFWs increased to $5.7 billion in 1997. However, in 1998 personal remittances declined to $4.1 billion.

Although the placement of overseas workers has declined further following the crisis, the depreciation of the peso has encouraged further increases in foreign exchange remittances of OFWs. These remittances have also boosted national economic growth, adding one half to one whole percentage point increase over the growth of domestic output.

4. Inflation Although inflation increased somewhat in the later months of 1997, stable food prices allowed the country to experience relatively tame inflation in spite of the large peso depreciation that accompanied the financial crisis. This is also in spite of the drought that adversely affected agricultural production. In anticipation of the food supply shortages that could arise because of the drought, the government imported rice and corn and this tempered inflationary pressures. The overall price stability may also be attributed to greater competition arising from a more liberalized trade and investment environment. It was the rise in prices of services and housing repairs, which accelerated in the months following the onset of the crisis, that exerted some pressure on overall inflation. Nevertheless, inflation was kept below the psychological double-digit threshold up to the first quarter of 1998 (Figure III.4).

In the second quarter of 1998 when the biggest drop in agricultural output was felt because of the worsening of the drought, the increase in food prices accelerated, bringing 12

the overall inflation closer to double digit levels. Food price increases continued and worsened towards the latter part of the year, this time due to the typhoons that hit the country in October. By year-end, the inflation rate reached 10.4% and increased further to 11.6% in January 1999.

5. Unemployment Following the slowdown in the economy in the second half of 1997, unemployment and underemployment rates slightly went up during the same period (Table III.3). In 1998, however, there was a more significant increase in unemployment primarily due to the contraction in agricultural employment which in turn was due to the dramatic drop in agricultural production. In the second half of 1998, the decline in employment in the industrial sector contributed to the worsening of the unemployment rate. Meanwhile, underemployment rates in 1998 were kept at about the same level as those in 1997.

6. Trade Gap With the large peso depreciation arising from the currency turmoil, the balance of trade improved although occurring with some lag. In the six months immediately preceding the onset of the crisis, imports still outpaced exports and the trade gap continued to widen. However, exports posted a stronger growth and imports started to show signs of slowing down. In 1998, imports declined drastically while exports continued to expand, thus turning the trade balance into a surplus (Figure III.5).

While total imports continued to expand in the second semester of 1997, consumer goods imports already dropped (Table III.4). In fact, consumer goods imports started declining as early as in the first semester. In 1998, however, imports nose-dived across all types of commodities. Capital goods imports dropped substantially especially in the second half of 1998. In spite of this, capital goods accounted for an increasing share of total imports: 40.8% in 1998 versus 30.4% in 1995. Meanwhile, raw materials, fuels, and consumer goods have accounted for a declining share of total imports in recent years.

The financial crisis seems to have slowed down the country’s export earnings but not to a very serious extent. While exports decelerated in 1998 especially towards the latter part of the year, it managed to grow by close to 17% for the year (Table III.5). This could be attributed to the fact that the country’s biggest market which is the U.S. continued to be healthy. Propping up exports growth are manufactured exports, led by electronic equipment and parts, which in 1998 expanded by more than 30%. Other big manufactured exports like garments and textile yarns and fabrics performed poorly.

Manufactured goods however continued to account for an increasing portion of total exports, from 79.5% in 1995 to 87.8% in 1998.

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7. Balance of Payments and International Reserves Position From balance of payments surpluses in 1994-1996, the country realized a deficit in 1997 (Table III.6). This occurred as early as in the first semester ($268 million) although the magnitude was much larger in the second half at $ 3.0 billion. After the start of the crisis, net foreign capital inflows dropped dramatically. Heavy withdrawals of portfolio investments from the country occurred at the start of the crisis. Net direct foreign investments, while still positive, were cut down by about half in the second semester of 1997 compared to their previous levels.

In the first half of 1998, the balance of payments position started to improve, posting a surplus of $ 1.56 billion. In addition to the significant narrowing down of the trade deficit, the country resorted to more foreign borrowings while portfolio investments began to trickle back. In the third quarter, however, the BOP position slightly deteriorated on account of larger principal payments and less capital inflows. As of endOctober 1998, the BOP position registered a surplus of $ 1.35 billion, a dramatic improvement from the $ 3.28 billion deficit in 1997. The government is expected to avail of a much larger amount of foreign borrowings in 1999 and this is anticipated to improve the country’s BOP position further.

With the deterioration in the country’s BOP position in the second half of 1997, gross international reserves dipped. From more than $ 11 billion prior to the crisis, GIR went down to $ 8.6 billion by December 1997, equivalent to only 2.8 months of merchandise imports as against 3.8 months prior to the crisis. In the first semester of 1998, international reserves level improved to $ 10.4 billion (end-June) as the country ‘s BOP position recovered and has risen further to $ 10.7 billion by end-1998 and to $ 11.5 billion in end January 1999 (Figure III.6).

8. Budget Deficit The financial crisis led to a squeeze in the government budget. On the one hand, revenues suffered largely because of the decline in imports and the slowdown in the economy. On the expenditure side, higher interest payments caused by the rise in interest rates and assistance requirements for drought- and typhoon-affected areas put greater pressure on budgetary resources.

From surpluses in 1994-1996 until the first half of 1997, the government started to post a deficit of P 2.3 billion in the second semester of 1997. This worsened to P 50 billion for the whole year of 1998 when marked revenue shortfalls were experienced.

The original program was a deficit of only P16 billion.

The fiscal impact of the crisis is further discussed in the succeeding chapter.

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IV.

FISCAL IMPACT OF THE CRISIS

1.

National Government Revenues and Expenditures

1.1

Revenues

Significant progress in tax revenue performance has been achieved, particularly in the late 1980s. Although some gains are still apparent in the mid-1990s, tax effort appears to have tapered off. Tax effort rose by a total of 3 percentage points of GNP in the four-year period between 1986 and 1990. In contrast, it only increased by 1 percentage point of GNP in the period 1992 and 1996. However, the slowdown in the upward trend in tax effort was masked by the large inflow of privatization proceeds (1.7% of GNP in 1994 and 1.2 % of GNP in 1995) (Table IV.1).

Thus, the national government posted a surplus in its fiscal position for the first time in more than 20 years in 1994. In 1995 and 1996, this feat was replicated (Table IV.2).

National government revenues started to falter in the last half of 1997 following the start of the Asian financial crisis. Tax revenues slipped from 16.4% of GNP in 1996 to 16.3% in 1997. The primary culprit was the dramatic shortfall in import duties which was P34.7 billion lower than target for the year. In contrast, the deficiency in collections of the Bureau of Internal Revenue was smaller at P3.1 billion (Table IV.3).

The tax revenue target of the national government for 1998 was reduced initially from P513.1 billion to P498.4 billion in February 1998 and then to P453.7 billion in June 1998. In spite of these adjustments, total tax collections still did not meet the target.

Total tax take reached P416.6 billion, P96.5 billion short of the original target. Of this amount, P51.9 billion was accounted for by the Bureau of Internal Revenue (BIR) and P45.2 billion by the Bureau of Customs (BOC). In toto, tax effort dropped from 16.3% of GNP in 1997 to 14.9% in 1998.

1.2

Expenditures

At the time of the preparation of the 1997 national government budget in the early part of 1996, the fiscal position of the national government has been in surplus for two consecutive years, the first time in more than 2 decades. The picture was rosy, maybe at its rosiest in recent history.

Thus, the 1997 budget of the national government (net of debt service) was expansive. It grew by 21.2% compared to the previous year’s growth rate of 13.5% and the 18.5% average in 1993-1997 (Table IV.4). As a proportion of GNP, it rose to 16.4% from 15.0% in 1996 (Table IV.5).

This expansive mood was carried over when the Executive branch formulated the 1998 budget in the first semester of 1997 as the national government continued to post a 15

surplus in 1996 and as the consolidated public sector itself posted a surplus for the first time in 20 years. Given this perspective, the President’s Budget (net of debt service) for 1998 was projected to grow by 12.4%, climbing to 16.7% of GNP (Table IV.6).

National Government Budget in 1998.

Despite the onset of the Asian financial crisis in July 1997, the 1998 President’s Budget was not downscaled when it was presented to Congress.

Moreover, Congressional initiatives led to an even larger budget appropriation. The expenditure obligation program based on the 1998 General Appropriations Act provided for total expenditures net of debt service equal to 18.5% of GNP (Table IV.6).

Concomitant with the downward adjustment in the revenue program in the early part of 1998, the national government expenditure program was similarly modified.

Administrative Order 372 was issued in February 1998 imposing a 25% reserve on total maintenance and operating appropriations of all national government agencies. At the same time, it imposed a 10% reserve on the IRA share of LGUs. Total national government expenditures net of debt service was cut by 14.9% relative to the programmed level under the 1998 GAA and by 5.5% relative to the programmed level under the President’s Budget (Table IV.6). Although national government expenditures net of debt service grew by 6.2% in nominal terms (Table IV.4), they actually declined by 3.5% in real terms in 1998. Thus, national government expenditures net of debt service contracted from 16.4% of GNP in 1997 to 15.8% in 1998 (Table IV.5).

Of the major expenditure items, those on economic services and national defense were the most adversely affected. Preliminary estimates of actual expenditure obligations for these sectors represented 30% and 17%, respectively, of their programmed levels under the 1998 GAA. Among the economic service sectors, water resource services and transportation/communication services suffered the deepest cuts relative to the 1998 GAA expenditure program. Actual national government expenditures in water resource development and transportation and communication for 1998 only reached 38.6% and 64.1% of levels under the GAA expenditure program. Moreover, national government expenditures on all the economic service sectors with the exception of agrarian reform posted negative rates of growth relative to their 1997 levels (Table IV.4). National government expenditures on infrastructure services (combined power/energy, water resources development and transportation and communication service sectors) also decreased from 2.5% of GNP in 1997 to 1.8% of GNP in 1998 (Table IV.5) On the other hand, expenditures on social services and general public services were relatively protected. On the average, the reduction in aggregate expenditures on these sectors was equal to only 10% of the GAA program levels (Table IV.6). This came about as the reserves earlier imposed on the social service sectors were selectively lifted.

Among the social service sectors, housing/community services and social welfare/employment services were the hardest hit by the fiscal austerity measures 16

enforced in 1998. Preliminary estimates of national government expenditure obligations in housing/community services and social welfare/employment services were just equal to 50.4% and 24.3%, respectively, of GAA program levels. Thus, expenditures on housing/community services declined in nominal terms during the year (Table IV.5).

Although allocation for the education and the health service sectors in 1998 were not reduced by as much as those of the other sectors relative to program levels, per capita expenditures on these sectors slid in real terms during the year (Table IV.7).

These developments are largely consistent with the experience during the crisis years of 1983-1985 when a reallocation of national government resources from economic services and national defense to debt service, general public services and social services was evident. However, unlike in the earlier period, general public services failed to be as resilient to the fiscal crunch in 1998.

In July 1998, the government announced the exemption of major departments engaged in the delivery of basic social services from the mandatory reserves (equivalent to 25% of non-personnel expenditures) earlier imposed on all government agencies.

However, the lifting of the reserves was not implemented immediately.3 Moreover, a slowdown in the release of Notices of Cash Allocation (NCAs) effectively restricted the spending of government agencies. Given this situation, government agencies naturally gave the payment of salaries of wages and salaries the highest priority. Thus, many agencies suffered delays in their expenditure obligation program as they postponed contracting for the supply of goods and services even if the allotment authority (i.e., the authority to obligate) was available in anticipation of inadequate cash availability. In cases, where procurement was not intentionally put on hold, existing suppliers and contractors paced their delivery of goods and services with their perception of government’s ability to pay for its obligations.4 It is also important to emphasize that government agencies/departments were given the discretion to decide which programs/activities will be given funding priority so that the impact of the fiscal austerity measures on actual expenditure obligations on various programs is largely uneven.

Department of Health (DOH). In the health sector, the procurement of drugs and medicine was most harshly affected by the financial crisis. The allotment authority for the acquisition of drugs and medicines that was actually released as of the end of September 1998 was equal to only 23.6% of the appropriation cover (Table IV.8). In the last quarter of 1998, allotment authority for another 63.1% of the appropriation cover was issued (Table IV.9). Undoubtedly, the delay in the release of the allotments for drugs and medicines contributed to the slowdown in their procurement. As of the end of December 1998, actual obligation for drugs and medicines represented a low 49.2% of allotments and 42.7% of appropriations.

In the case of the regional assistance for drugs and medicines, there is no slack between obligation and allotment. But just the same, only 75% of its appropriation was supported by an allotment authority.

3

In the Department of Health, for instance, it was not until the last quarter of 1998 that the lifting of the mandatory reserves was actually lifted.

4 The accounts payable of the government piled up towards the end of 1997, amounting to P108 billion.

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The dramatic cutback in the expenditure obligation for drugs and medicines coupled with the 25%-30% increase in the price of drugs following the depreciation of the peso in mid-1997 implies a critical contraction in the supply of drugs and medicine in the public health sector. What makes this situation worse is the fact that this comes at a time when households themselves have little resources to supplement what the public health care system is able to provide.

The delay in the restoration of 25% mandatory reserves is an oft-repeated tale in the DOH. Only 72.8% of appropriations in public health services were supported by allotment authority as of the end of September 1998 (Table IV.8). Within this sub-sector, the most badly hit activities are: family health program with allotment cover equal to 50.1% of appropriations, the MOOE portion of physicians for doctorless communities (54.7%), community health program (56.2%), STD/AIDS control program (59.9%), noncommunicable disease control program (62.5%), the expanded program of immunization (68.7%), primary health care (70.0%), dengue control (75.0%), rabies control (75%) and tuberculosis control (75.8%). Additional allotment authority was issued in the last quarter of 1998 such the allotment-to-appropriation ratio for most of these programs surged to 95% (Table IV.9). However, the ratio for STD/AIDS control, the MOOE portion for physicians for doctorless communities, and primary health care remained in the vicinity of 75%.

Moreover, actual delivery of services appears to be adversely affected as the obligation-to-allotment ratio reached an average of only 53.1% for public health services as a whole as of end of December 1998 (Table IV.9). In particular, the ratio for maternal and child health services, nutrition services, expanded program of immunization, family health program, and the MOOE portion of physicians for doctorless hospitals were all below 50%. In the case of immunization, there is some data, albeit incomplete, that tends to show a decline in the proportion of fully immunized children in 1998.

Department of Education Culture and Sports (DECS). With over 80% of its total budget earmarked for personal services, the DECS has very little room to maneuver in times of fiscal restraint. Thus, in 1998, it found itself having to reduce the allocation for key educational inputs like textbooks, desks, school buildings and teacher training. In particular, obligation authority (or allotment) for desks, chairs, textbooks and instructional materials amounted to only 37.7% of total appropriation cover (Table IV.10). To make matters worse, no expenditure obligations were actually made for this expenditure item as of the end of December 1998. This situation aggravates the existing textbook shortfall. Note that textbook-pupil ratio currently stands at 1:8.

In a similar vein, the allotment-to-appropriation ratio for land and land improvement was a low 19.6% while those for teacher training and Government Assistance for Student and Teachers in Private Education (GASTPE) were 63.4% and 75.0%, respectively. On a positive note, the gap between allotments and obligations for these items was nil. Enrolment figures in both elementary and secondary levels were lower than normal in 1998. This may be attributable to households’ inability to provide

18

the out-of-pocket costs5 of education even in public schools which have been estimated to amount to 27.8% of total unit cost (or P1,830) at the elementary level and 41.2% of total unit costs (or P3,030) at the secondary level. This result indicates the need to re-examine and rationalize the government’s scholarship program (particularly the GASTPE) in terms of both coverage and support level.6 The appropriations for two items (new teacher positions and to fund newlylegislated high schools) were largely left unfunded. The allotment-to-appropriation ratio for new teacher positions was 24.1% while that for new high schools was 47.9% in 1998.

While these items may not be that critical given efficiency considerations, it cannot be denied that the funding shortfalls may cause short-term problems.7 Department of Social Welfare and Development (DSWD). The most severely reduced programs of the DSWD were the assistance to persons with disability (with an allotment-to-appropriation ratio of 41.8% as of end of September 1998) and calamity relief operations (45.7%).8 All of its locally funded projects, including the Comprehensive and Integrated Delivery of Social Services (CIDSS) had ratios equal to 75% (Table IV.11).

It is notable, however, that absorptive capacity of the DSWD is rather high. The obligation-to-allotment ratio in most activities is close to unity.

National Government Budget in 1999 With the government’s fiscal difficulties continuing in 1999, aggregate national government expenditures net of debt service (based on 1999 GAA) will further decline from 15.8% of GNP in 1998 to 15.2% (Table IV.5).

National government expenditures on economic service sectors will post some recovery. Aggregate expenditures on economic services is the fastest growing major expenditure item in 1999. Thus, expenditures on infrastructure will inch upward from 1.8% of GNP in 1998 to 1.9% of GNP in 1999 (Table IV.5). Also, expenditures on both agrarian reform and agricultural services will register substantial growth (Table IV.4). In spite of this, agriculture expenditures in 1999 will stand at 0.6% of GNP, 25% lower than the 0.8% average in 1975-1992. This appears to be rather inconsistent with policy pronouncements giving priority to the agriculture sector.

On the other hand, it is worrisome that national government per capita expenditures on education and health services will decline again in real terms in 1999.

This will be the second year in a row that this is occurring.

5

Out-of-pocket costs include expenditures on transportation, textbooks and supplies but not uniform.

It has been shown that the support level of the Education Service Contracting (ESC) and the Tuition Fee Supplements (TFS) are low such that only families which are relatively better off are able to leverage own resources and enjoy the benefits of these schemes.

7 It has been pointed out that the high pupil-teacher ratio in public schools is traceable not so much to a real shortage in the number of teachers in the DECS payroll but to problems with deployment of teachers.

8 Data for end of December is not yet available.

6

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2.

LGU REVENUES AND EXPENDITURES

2.1

Revenues

The fiscal austerity measures undertaken by the government in the light of the Asian financial crisis has had an adverse effect on local government finances. Early in 1998, the national government announced that it will withhold 10% of the IRA share of LGUs. Although 50% of the total amount withheld was eventually released to LGUs, the unfreezing of the mandatory reserves was made very late in the last quarter of the year such that for all intents and purposes LGUS were operating within the more restricted fiscal framework for the most part of the year. In fact, approximately half of the LGUs in our sample reported that the partial lifting of the reserves was only operationalized in January of 1999.

The imposition of a 10% reserve on the IRA share of LGUs essentially implies a measly 2.6% growth in the IRA level in 1998 while a 5% reserve means that on the average the 1998 IRA is 8.3% higher than its 1997 value. Compare these figures with the projected 14.0% growth in the IRA in 1998.

Over and above the reduction in their IRA shares, many LGUs likewise registered a decline in locally generated revenues. This situation is true in 7 out of the 20 LGUs in our sample (Table IV.12). In these LGUs, total locally generated revenues decreased by 0.9% to 49.8% in 1998.

The shortfall in LGU revenue inflows from local sources appears to be largely driven by significant reductions in nominal real property tax (RPT) collections. The RPT collections of rural LGUs appear to be more adversely affected than those of urban LGUs. Thus, 7 out of the 11 municipal local government units (MLGUs), 2 out of the 4 provincial local government units (PLGUs) and 2 out of the 5 city local government units (CLGUs) in our sample had lower RPT revenues in 1998 relative to 1997. The reduction in RPT collections ranged from a low of 1.1% to a high of 29.5%.

In contrast, non-RPT tax revenue collections of CLGUs exhibited a greater tendency to decline in 1998 compared to those of MLGUs and PLGUs. Note that nonRPT tax revenues in 2 out of the 5 CLGUs decreased in 1998 while only 2 out of 11 MLGUs had a similar problem.

But what perhaps caused greater dislocation in local government finances in 1998 is the overall shortfall in LGU revenues relative to projected or programmed levels.

Actual local source revenues in 15 out of the 20 LGUs in our sample were lower than target levels in 1998. The revenue gap (i.e., the difference between actual collections and target levels) was substantial in most LGUs, ranging from 4.5% to 92.4% of actual collections (Table IV.12).

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2.2

Expenditures

Because projected revenues are generally higher than their actual receipts in 1998, LGUs had to adjust their actual expenditure obligations and disbursements accordingly.

The expenditure response of LGUs to the fiscal crunch is similar to that of the national government. Many LGUs imposed an across-the-board 25-30% cut on non-personnel recurrent expenditures (or maintenance and other operating expenditures, MOOE, in Philippine parlance). A few responded on a more targeted basis, i.e., they secured expenditures in programs and projects that are high on the priority list of local chief executives while implementing greater cuts on other items.

Comparing programmed/appropriated expenditure levels with actual obligations, LGU expenditures on economic services and other purposes were the most severely affected by the fiscal cutback in 1998 (Table IV.13). In particular, the expenditure share of economic services in total actual obligations in 10 out of the 20 LGUs in our sample declined relative to the sector’s share in total appropriations. In the other LGUs, it is the share of other purpose expenditures in total obligations that was reduced relative to their share in total appropriations.

In contrast, LGU expenditures on general public services (consisting of general administration and police services) were the most resilient to the financial crisis. The share of general public service sector in actual total obligations was considerably higher than its share in total appropriations in 16 out of the 20 LGUs in our sample. This may be explained by the fact that LGU expenditures on general public services are largely composed of wages and salaries which remain untouched even when there is a fiscal crisis.

In like manner, share of the social service sectors in total actual LGU spending is slightly higher (or, at the very least, just about equal) to its share in total LGU appropriations in 15 out of the 20 LGUs in our sample. In this sense, LGUs accorded some degree of protection to the social sectors (Table IV.13).

However, the picture is not that rosy when one looks at the level of real per capita LGU spending. Although LGUs appeared to have been partly successful in putting up a firewall around social sector budgets by maintaining the expenditure shares of the sector, actual levels of LGU expenditures in real per capita terms posted some deterioration in 1998.

Per capital total LGU expenditure fell in real terms in 13 out of the 20 LGUs in our sample in 1998 (Table IV.14). Moreover, per capita real total social service expenditures declined in 10 LGUs in our sample.

Although per capita LGU expenditure on personal services declined in only 9 of these LGUs, real per capita MOOE and capital outlays were reduced in 12 of these LGUs in 1998.

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One of the areas that is badly hit by the fiscal bind is MOOE in the basic health sector. In particular, per capita MOOE spending in basic health services declined in 13 out of the 20 LGUs for which we have data. This situation severely affected the availability of drugs and medicines in barangay health stations, rural health centers, and devolved hospitals and was consistently noted by FGD participants in most areas.

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V.

1.

SOCIAL IMPACT OF THE FINANCIAL CRISIS

Labor Market

The regional financial crisis and the abnormal weather pattern affected adversely the employment situation in the Philippines. Firms resorted to retrenchments, temporary lay-offs and reduced working hours as demand slackened and costs of production went up. Workers in the agricultural sector, meanwhile, had to contend with higher underemployment due to the drought.

Although massive lay-offs were not noted, the crisis and the drought hampered the economy from absorbing the new entrants to the labor force. This contributed to a higher unemployment rate, which was already considerable even before the crisis.

1.1

Labor Force Participation

The labor force participation rate (LFPR) declined for five quarters from July 1997 to July 1998 compared to the year-ago rates (Table V.1). The labor force participation rate was 66.3% in July 1996, declining to 65.7% in July 1997, and further to 64.9% in July 1998. However, stating October 1998, the labor force participation rates increased slightly relative to the same quarter of the preceding year.

The decline in the LFPRs are more pronounced in the 15-19 and 20-24 age groups. The observed decline in the LFPR could be attributed mainly to the increase in the number of individuals 15 years old and over who have opted to go to school rather than join the labor force. This could be because of the belief that there is no work available for them. This is substantiated by the data from the panel of households from the labor force surveys.

1.2

Unemployment and Underemployment9

Unemployment When the regional financial crisis struck in July 1997, the unemployment rate was 8.7%. Since then, the unemployment rate for the next 6 quarters has been higher than the corresponding quarter of the previous year. The largest percentage increase in the unemployment rate was observed in April 1998 when it rose to 13.3% from 10.4% a year ago owing to the combined effect of the financial crisis and the El Ni単o. The unemployment rate has risen to 8.9% in July 1998 and 9.6% in October 1998 and 9% in January 1999 (Table V.2). This translates to a pool of 2.8 million unemployed Filipinos in 1999.

9

The analysis in this section is largely based on the quarterly labor force surveys conducted by the National Statistics Office.

23

The seesawing pattern observed in the unemployment rate is due to seasonal factors, i.e., unemployment rate is higher in the April rounds due to the influx of students on summer vacation who are looking for work.

Using the October survey results, total employment increased from 27.4 million in 1996 to 27.9 million in 1997 and 28.3 million in 1998 (Table V.3). The increase in available jobs was not enough to absorb the increase in the labor force. In 1998, the labor force increased by 1 million to 31.3 million. Consequently, the unemployment rate went up from 7.4% in 1996 to 7.9% in 1997. In 1998, it shot up to 9.6%.

Despite the improvement in the weather, the unemployment rate rose to 9% in January 1999, from a low of 7.7% in January 1997 to 8.4% in January 1998. This indicates the continued effect of the financial crisis on the economy.

Sectoral Impacts Employment in the industry sector fell. Among the industry subsectors, construction, manufacturing, and mining and quarrying were badly hit. Between October 1997 and October 1998, construction reduced its workforce by 130,000, while manufacturing laid off 68,000 employees (Table V.3). Mining and quarrying suffered a loss of 20,000 workers.

Employment in the agriculture sector declined by 191,000 between October 1996 and October 1997 due mainly to the El Ni単o. In October 1998, the sector was able to absorb additional 12,000 workers but this is still below the level in October 1996.

Meanwhile, employment in the services sector continued to increase as displaced workers flocked to this sector. The wholesale and retail trade, transportation and communication, and community, social and personal subsectors provided additional 546,000 jobs in 1997 and 563,000 jobs in 1998. On the other hand, after suffering a setback in 1997, employment in the financing sector expanded in 1998, albeit at a much lower growth rate than before the crisis.

Underemployment Based on the October rounds of the labor force surveys, the underemployment rate rose from 19.4% in 1996 to 20.8% in 1997 and to 23.7% in 1998 (Table V.2). This supports the observation at the focus group discussions that workers had to settle for less working time than be laid off. Moreover, the displaced workers and the rest of the population, particularly the poor, tried to find some form of employment, even part-time work, in order to generate some income.

Urban-Rural Impacts The financial crisis and the El Ni単o exacted tolls on both the urban and rural labor markets. The unemployment rate in the urban areas rose to 12.1%, representing 1.8 million unemployed. The unemployment rate in the rural areas rose to 7.4%, and this

24

translates to 1.2 million jobless persons. The underemployment rate has surged to 20.6% in the urban areas and 26.3% in the rural areas as of the fourth quarter of 1998.

Regional Impact Looking at the July 1997 and July 1998 data, unemployment rate has risen in NCR, CAR, Region 2, Region 5, Region 7, Region 9, Region 11, Region 12, and CARAGA. Based on the October rounds, the unemployment rate has increased in all regions. In October 1998, unemployment rate is highest in NCR at 15.1% and lowest in Region 2 at 4.1%.

By Age Group and Educational Attainment The older and presumably, more skilled workers were better able to hold on to their jobs. The proportions of employed persons who are in the 15-19, 20-24, and 25-34 age groups fell while the proportion of employed persons in the older categories increased (Table V.4). In July 1997, the proportion of workers who are 15-34 is 46.5%; this has gone down to 45.5% in July 1998. This went down further to 45.1% in October 1998.

The more educated workers are getting the available work. The proportion of employed persons whose educational attainment is below high school graduate decreased while the proportion of employed persons who are at least high school graduate increased.

Despite the increase in the number of employed males and females, the unemployment rate for both groups also went up. The share of female workers to total employment grew. Some FGDs reported that when the male spouses lost their jobs, the women took on direct selling, laundry and other odd jobs to augment family income.

1.3

Overseas Filipino Workers

The regional financial crisis has affected the deployment of Overseas Filipino Workers. The number of OFWs deployed increased slightly by 1% from 747,696 workers in 1997 to 755,684 in 1998 (Table V.6). This is very much lower than the 13% growth registered in 1997. The number of sea-based OFWs grew by 2.6%. On the other hand, the total number of land-based OFWs expanded by 0.6%.

The marginal increase in land-based OFWs could be traced to fewer job opportunities in Asia. Deployment to Asia dropped by 6% in 1998 (Table V.7). This translates to 14,000 displaced OFWs last year. Countries such as Hong Kong, Singapore and Malaysia, which are among the top destinations of OFWs, were forced to cut back on the hiring of new workers as a result of the regional financial crisis.

The number of Filipino workers sent to Hong Kong fell by 18.3% to 64,160.

Deployment to Singapore fell by 16.7% to 13,373 while deployment to Malaysia dropped by 65.7% to 4,660.

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Meanwhile, deployment to the Middle East, which regained its position as the top destination, grew by 2.6%. Moreover, deployment to America, Europe and Africa increased but these were not enough to compensate for the decline experienced in Asia.

It surfaced in the FGDs that households who have members working abroad benefited from the higher peso value of the dollar remittances. A few OFWs were sent home, but this was mostly due to reasons other than the economic crisis.

Remittances of OFWs declined by 13.4% from $5.15 billion in January– November 1997 to $4.46 billion during the same period in 1998 (Table V.8).

Remittances of sea-based workers declined minimally by 0.2% to $239 million, while remittances of land-based workers declined by 14% to $4.22 billion.

Records of the Bangko Sentral ng Pilipinas indicate that remittances of OFWs from January to November 1998 fell to $4.46 billion. However, while remittances of OFWs declined in dollar terms by 13%, the peso value went up by 20%.

Remittances by OFWs in Singapore declined by 20.7% while remittances by those from Hong Kong decreased by 3.4%. Incomes of OFWs in Hong Kong were cut recently.

1.4

Firms

The data of the Department of Labor and Employment based on the reports of establishments indicate that the crisis has a significant impact on firms and workers.

There has been an increase in the number of firms that closed or retrenched due to economic reasons. In 1996, it was 1,079; in 1997, it went up to 1,155; and in 1998, it jumped to 3,072 (Table V.9).

The impact seems to be greater in NCR compared to areas outside NCR. NCR experienced the largest increase in the number of affected firms with 1,708 that closed or retrenched in 1998 (Table V.10). This was triple the number in 1997. Central Visayas had the second largest number of affected firms at 268 in 1998, followed closely by Southern Mindanao with 257 affected firms.

The manufacturing, wholesale and retail trade, and financing, insurance, real estate and business services subsectors were heavily affected. There were 1,025 manufacturing firms that were affected in 1998, double the number in 1997 (Table V.11).

There were 600 wholesale and retail firms that closed in 1998, more than triple the number the previous year. Almost 500 firms engaged in financing and real estate either closed or retrenched, more than three times the number in 1997. Construction was also hit, with 173 firms that either closed or retrenched.

Consequently, there has been a drastic increase in the number of workers who were permanently or temporarily laid off, or had reduced working time. The total number workers affected was 62,724 in 1997 which dramatically rose to 155,198 workers in 1998 (Table V.12). The number of permanently laid-off workers increased by 96%, temporarily laid-off workers by 156 % and the number of workers with reduced working 26

time by 648%. The figures indicate the kind of coping mechanisms utilized by firms and the extent to which it had affected workers.

The end-1998 figures however, show that the restructuring is waning. The number of affected workers declined from more than 12,000 in October, to more than 8,000 in November and down to about 4,900 in December.

1.5

Impact based on Focus Group Discussions

Although massive layoffs were not observed, loss of gainful employment was noted among many communities as reflected in the FGD reports. Construction, real estate, manufacturing, and agriculture seemed to be among the hardest hit sectors.

Loss of jobs was felt largely by fishing communities, urban poor and middle income communities.

1.

Farmers and fisherfolks were hardest hit by the crisis and El Niño

The FGD participants reported that the crisis and El Niño forced many farmers and fisherfolk to abandon their jobs (whether temporarily or permanently) for more viable sources of livelihood. Reasons varied. First is the lack of control over the prices at which they sold their produce to traders (an oppressive situation that existed long before the crisis hit). Second are the crisis-driven increases in the costs of basic inputs.

The diminished use of farm/fishing inputs resulting from crisis-driven price increases (along with such elements as poor irrigation facilities, competition with commercial fishing vessels and weather disturbances such as La Nina and El Niño) contributed to lower farm yield/fish catch.

In Kalanganan, Cotabato for instance, serious flooding destroyed the fishponds that were the main source of income for most residents. Repairing the damage became difficult for many because of high input prices. As a result, many small fishpond owners had to sell-out to big fishpond owners.

2.

“Free lance” laborers were also affected

“Free-lance” daily wage laborers whom FGD participants in Baguio and Benguet referred to as the “por dia workers” were among the hardest hit. With the onset of the crisis, opportunities to work--which from the start were already irregular--became even scarcer and more difficult to access.

3.

There were cases of employee retrenchment and displacement

With the onset of the crisis, formal employment (particularly the blue- and lower white-collar workers) appears to have become less of a viable source of income for many poor families.

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Communities largely dependent on employment were directly hit by retrenchment policies initiated by the business sector. Of this, 39% came from the middle income, 43% from the urban poor, 23% from farming and 50% from fishing communities. Factory closures affected 31% of middle income communities. Forty three percent of urban poor communities complained of huge unemployment problems due to the slowdown in real estate and construction industries which resulted in the slack demand for construction workers and other semi-skilled and non-skilled laborers. (Table V.13) The household survey provided some interesting insights on the problems in the labor market. More than 45% are unemployed. There are over 51% unemployed persons in sustenance farm communities. The unemployed females in all communities outnumbered males by a ratio of almost 2:1 (Tables V.14 and V.15).

In the last 18 months, 8% of the labor force lost their jobs. Of these, 12% was from middle income communities. The others were: 10% from the urban poor, 8% from the upland, 5% from the sustenance farm, 5% from the commercial farm and 4% from fishing communities.

There were various reasons for unemployment. Eighteen percent blamed retrenchment as the primary reason. Twelve percent said that they were simply lazy and were not really looking for work. Nine percent said that there were no opportunities available. Six percent said that they changed residence while some 4% did not have any capital to start or continue their business (Table V.16).

These phenomena at the sub-national and national levels strongly indicate that gains in efforts to broaden the base of the economy through market reforms are being reversed.

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2.

Poverty and Income Distribution

2.1

Incomes

Incomes declined for many households. More households seem to have been adversely affected compared to those who have benefited from the crisis. Available data also suggest that the poor have suffered more.

MIMAP Simulations Simulations done by Reyes (1998) using the MIMAP models show that the economic slowdown due to the financial crisis and the El Ni単o would have resulted to declines in the average income for the different deciles. The percentage declines range from a low of 4.6% for the richest decile and a high of 7.3% for the poorest decile (Table V.17) Annual Poverty Indicators Survey The results of the 1998 Annual Poverty Indicators Survey (APIS) and the 1997 Family Income and Expenditure Survey tend to support the simulation results obtained by Reyes, except for the richest decile. The data show that per capita income declined by 3.6% in nominal terms and by 12.1% in real terms (Table V.18). Moreover, the average family income of all deciles except for the richest decile decreased (Table V.19). The percentage decline is greatest for the lowest income decile at 29%.

The 1998 APIS also revealed that 17% of families experienced reduced wages.

The richest 60% seems to have been more affected as 18% of the families in this group had reduced wages compared to 15% of families in the poorest 40%.

Household survey The results of the household survey done in connection with this study indicate that 53% of households did not experience change in income as a result of the crisis.

Thirty percent suffered reduction in incomes while 17% had higher incomes now than during the pre-crisis period. Half of the households in the upland communities and 40% of households in sustenance communities had lower incomes. On the other hand, less than 20% of households in middle income communities had lower incomes.

The major reasons cited for the decline in incomes were: poor harvest mainly due to bad weather (38%); lower price for their produce (18%); reduced number of earning members (12%); reduced financial support from relatives (8%) and retrenchment from work (6%). Farming and fishing communities ranked poor harvest (62%) as the number one cause for the decrease in their income. Households from middle income communities, on the other hand, considered the reduction in the number of earning members (61%) as the principal factor that contributed to the deterioration of their income. Among urban poor communities, the reduction in the financial support from their relatives (35%) and retrenchment from work (26%) were the two most important reasons for experiencing reduction in income.

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Seventeen percent of the households claimed that during the period under review, their income had in fact increased. Among households in middle income communities, 23% claimed an increase in household income.

The major reasons that contributed to the increase in income include: promotion in job (22%); increased number of earning members (14%); new or additional work (12%); favorable prices for their outputs (6%); and increased harvest coupled with good weather (3%). About 25% of households from upland communities claimed that part of their additional income was derived from winnings in gambling. A few households from the middle income (6%) and urban poor (7%) communities, on the other hand, said that they availed of some credit to augment their income. In the middle income community, over 60% of the households said that their additional income came primarily from promotion in job. New or additional work (29%) and increased financial support from relatives (36%) were the two most important factors that contributed to improvements in the income of households from urban poor communities.

Focus Group Discussions Many participants experienced lower incomes during the crisis period. However, there were a few who reported increase in incomes.

2.2

Purchasing Power

Prices of goods and services increased significantly due to the drought and the financial crisis. Prices of food items rose significantly. Sharp increases in transportation fares and in the prices of utilities, clothing and education were also noted. The acceleration in inflation, coupled with reduced incomes, shrank the purchasing power of households considerably.

While it is true that not all households experienced declines in incomes, everybody suffered from higher prices. The 1998 APIS show that 97% of the families were affected by higher prices of food and other basic commodities.

The impact of the crisis took some time to take effect. The sharp depreciation of the peso in the latter half of 1997 was offset by the decision to draw down on existing inventory. The increased competition arising from the liberalization efforts of the government and the dampened demand somehow averted the immediate hike in prices.

However, in 1998, all the inventories had to be replenished at the higher exchange rate.

Interest rates went up too, thus, prices of consumer items followed suit.

Prices of consumer goods rose by an average of 5% in 1997 as indicated by the consumer price index. In 1998, the depreciation of the peso as well as the effects of the El Ni単o caused the inflation rate to rise to 9%. Food prices increased by 6.4% in 1998, after posting a low inflation rate of 1.7% in 1997. Non-food prices also increased significantly led by services and housing and repairs (Table V.20).

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The rate of price increases varied across regions (Table V.21). ARMM experienced the largest increase in consumer prices with an inflation rate of 13.7%.

Southern Mindanao came next with 12.4%, Ilocos with 9.6%, Western Mindanao with 9.6%, Southern Tagalog with 9.4%, Northern Mindanao with 9.4%, and NCR with 9.3%.

Central Mindanao experienced the lowest inflation rate in 1998 with 7.4%, followed by Central Visayas with 7.5% and Western Visayas with 7.6%.

The increase in prices implies a decline in the purchasing power of the households. In a span of 21 months, the peso has lost 14% of its value. Thus, one peso in March 1999 is less than nine-tenths of the value of the peso during the pre-crisis period (June 1997). This means that to be able to buy the same basket of commodities valued at P100 in June 1997, one has to spend P116 in March 1999. The increase in prices coupled with the decline in income translates to a much bigger decline in the purchasing power of households.

Focus Group Discussions and Household Survey Many FGD participants lamented that such sharp increases in prices were not matched by corresponding increases in wages and earnings. Thus, the net result was a weakened purchasing power and a decrease in access to basic necessities. The focus group discussions and the household survey provided more detailed information on how households were affected by the increase in prices. The major impacts include the following: a) There was a widespread spiralling of prices; some households were forced to forego buying/consuming some goods.

The crisis forced more than 40% of the households to refrain from buying certain goods they used to enjoy before. Ninety-three percent cited high prices as the single major reason that prevented them from buying these items (Table V.22).

In one middle income community for example, an FGD participant said in jest that the crisis made him stronger. He said that before the crisis, he had to exert effort to be able to carry grocery items worth P1,000. Today, he could easily swing the P1,000 worth of groceries since the bag contains very little. b)

In general, households maintained 3 full meals a day.

Despite the hard times, 98% of the households was able to maintain 3 regular meals daily. The decrease in the number of meals taken was in fact, more of an exception (Table V.22).

No one from the farming and fishing communities reduced the number of meals taken. There was a reduction of meals to two in 4% of urban poor communities and 2% of middle income communities. Two percent now have irregular meals (Table V.23).

However, 20% of the households who used to eat only two meals a day before the crisis could now eat three meals a day.

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Over 50% of those who reported reducing the frequency of regular meals said that they were forced to do it since over a year ago. Thirty percent has been practising it for about a year. The rest were equally divided between the group who was forced into it six months ago and those who were into it only a month ago (Table V.22). c)

There were major alterations in the household budget (Tables V.22 and V.23).

Home-prepared food. Forty percent said that the cost of preparing food for one’s household had increased. Sixty percent of the households from sustenance farm and 32% from the middle income communities shared this opinion.

Majority felt that the increase of food price in the market caused a 25% rise in the household food budget. About a fifth believed that it was much higher. Half of commercial farm communities said that it increased by 10%. About 48% of upland communities thought it went up by 25%. Thirty percent said that it did not go beyond 10%. Others noted a 50% increase. In the sustenance farm communities, 36% noted a 10% increase. However, an equal number said that it increased by up to 50%.

On the other hand, 18% said that their food budget actually decreased. Most had 25% reductions. Many households from middle income communities had 50% cuts.

Over 50% of the households from middle income communities reported that despite the crisis, they were able to maintain their usual food budget. About 30% from the rest of the communities concurred with this view.

Dining out. There were big cuts in dining-out expenses. About 18% claimed that they decreased their budget for dining out. A fifth in this group reduced their budget by as much as 75%. Over 30% of households from middle income communities and 21% from urban communities reported significant cut in their budget. About a third said that reductions were up to 50%. Over a fifth claimed that the cut in their dining out budget exceeded 50%. Fifty eight percent of urban poor communities cut their dining out expenses by more than 75%.

Clothing. While over 30% of the households said that they were able to maintain the same level of budget for clothing, some 29% averred that budget for children’s clothing increased. About 40% thought that the increase was between 5-10%. Over a third felt that the budget increased by more than 10%. Meanwhile, about 19% of the households had decreased budgets. Thirty nine percent were able to decrease clothing expenditure budget by as much as 50%.

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For adult’s clothing, 22% of the households increased their budget. Of them, 44% made up to 10% adjustment. Twenty percent said they had budget reductions, while 35% said that they made 50% cuts.

School Fees, Transportation, Medical Expenses, Housing and Utilities. Forty eight percent had to shell out more for their children’s education. Some 42% of the total households made 25% increases. Sixty eight percent of fishing households allotted more money. Of this, 53% had to effect as much as 25% increase. Fifty six percent of urban poor households only made up to 10% adjustment. Very few said that they reduced their expenditures for this.

As much as 45% of households from sustenance farm communities said that they had to increase the allocation for transportation of their children. Forty one percent in this group and 33% from the middle income claimed to have increased their budget for their children’s transportation by more than 25% of their pre-crisis budget.

Fifty five percent of all households had to increase their household budget for health care to cope with the increased costs of medicine and medical fees. About 40% increased their health care budget by up to 25%. Another 39% claimed to have made up to 10% increase.

At least 47% of all households had to appropriate additional money for housing expenses including monthly rental fees. Forty two percent in this group said that they made up to 10% adjustment, while 30% claimed that they had to add up to 25%.

Among all expenses, utilities was adjusted by the highest proportion of households. Sixty two percent of all households said that they had to increase their budget for this expense item; 41% claimed to have made up to 10% adjustment; and 28% percent said that they had to effect up to 25% increase. Among farming communities, at least 15% provided for up to 50% more than what they used to set aside before the crisis to pay for electricity, water and fuel.

2.3

Income Distribution

The combined effects of the financial crisis and the El Niño have served to reduce incomes of the households and contributed to a further worsening of the income distribution. There has been an increase in income inequality as manifested by the increase in the GINI ratio from 0.451 in 1994 to 0.496 in 1997 based on the 1994 and 1997 FIES. The share of the poorest quintile to total income has declined from 4.9% to 4.4% during the same period. Meanwhile, the share of the richest quintile rose from 51.9% to 55.8%. The ratio of the richest quintile to the poorest quintile has gone up from 10.6 in 1994 to 12.7 in 1997.

As discussed in Section 2.1 simulations done by Reyes (1998) using the MIMAP models show that the financial crisis and the El Niño would have resulted to declines in the average income for the different deciles but the percentage declines are greater for the lower income groups (Table V.17). The lowest 4 deciles experienced contractions in income ranging from 6.7% to 7.3%, with the poorest decile obtaining the biggest 33

percentage decrease. The higher income groups were not spared either, although the richest decile suffered the lowest contraction of 4.6%. Consequently, the GINI coefficient increased indicating greater income inequality.

This pattern is also supported by the data from the National Statistics Office.

Notwithstanding the differences in the methodology, the 1998 Annual Poverty Indicators Survey and the 1997 Family Income and Expenditure Survey show that all incomes of all deciles have declined between 1997 and 1998 (Table V.19). Furthermore, the share to total income of the lowest 90% has declined while the share of the richest decile has increased. The share of the poorest quintile has gone down from 4.4% to 3.4% while the share of the richest quintile has increased from 55.6% to 59.0% (Table V.24). In 1998, the ratio of the richest quintile to the poorest quintile has increased further to 16.4. This suggests greater income inequality.

2.4

Poverty

The reduction in incomes and the increase in prices are expected to worsen further the poverty situation. While there has been a reduction in poverty incidence from 35.5% in 1994 to 32.1% in 1997, the absolute number of poor families increased by 22,217 to 4,553,387 families. More than 70 percent of the poor or 3,307,215 families are in the rural areas.

Self-Rated Poverty The household survey conducted as part of this study reveals that there has been an increase in self-rated poverty from 40% just before the crisis to 43% in January 1999.

Some households sank below the poverty threshold while others were able to get out of poverty. Of those households who considered themselves poor in January 1999, about 10.3% were not poor before the onset of the crisis. Of those who are non-poor now, 2.5% were poor before.

More than half of the households in fishing and upland communities rated themselves poor. Forty eight percent of households in urban poor communities considered themselves poor. Only 21% of households in middle income communities considered themselves poor in 1999.

Thirty-eight percent of households indicated that their well-being improved since June 1997; 30% said that there was no change; and 31% claimed that they are worse off.

Sixty two percent of households in upland communities said that they are worse off now.

The corresponding figure for households in fishing communities is 53% and in urban poor households, 43%. The least adversely affected are the middle income communities where only 20% are worse off.

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The surveys of the Social Weather Station also indicate an upward trend in selfrated poverty between 1997 and 1998. In the April, June and September rounds, 58% of the sampled respondents considered themselves poor. In December 1997, the proportion rose to 63% and went up further to 64% in March 1998. In September 1998, the selfrated poverty was 62%.

While the increase seems to be small (3 percentage points based on the household survey and 4 percentage points based on the SWS survey), it is still a cause for concern since the poverty incidence is already high to begin with.

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3.

Human Development

3.1

Health, Nutrition and Population

Expenditures in health are motivated by both consumption and investment motives. The consumption motive is driven by the fact that good health is necessary to enjoy other goods and services. Better health and nutrition are known to raise labor productivity as well as improve the performance of students (Behrman 1990). These considerations underlie the investment motive. Essentially, for almost identical reasons that people invest on education, people also invest in their health and that of their children. Fertility, on the other hand, has a direct impact on the health of the child and the mother and is likewise affected by the health and nutrition status of the mother. In times of a crisis, people tend to become short sighted and are prone to foregoing expenditures when benefits accrue only over the longer term. For instance, preventive care and expenditures on public health is often sacrificed in favor of curative care.

Using macro level data, Lim (1998) pointed out that infant mortality is positively correlated with inflation rate and negatively correlated with GNP per capita. General mortality rate, on the other hand, is positively correlated with unemployment rate and negatively correlated with a 4-year moving average of GNP. These imply, Lim pointed out, that the crisis, which is characterized by decline or stagnation of GNP and higher unemployment, would mean higher infant and overall mortality rates.

Using household data, Orbeta and Alba (1999) have computed larger income and price elasticities of demand for outpatient care for poorer households compared to richer ones. This means that a price increase (one of the primary effects of the financial crisis) will adversely affect the demand of the poor more than the rich households. In addition, home care and public clinics have income elasticities that are negative which means that households consider these sources of care as inferior. Thus, a decrease in income due to the crisis is expected to increase dependence on home care and in public/charity clinic.

Using this model, Reyes and Mandap (1999), simulated the impact of the crisis on the choice of outpatient care. The study pointed out that there would be an increased demand in home care and health care public/charity clinics because of the crisis. This would mean more resources are need in the public clinics to meet this increased demand. Using a similar model for food demand in Orbeta and Alba (1998), Reyes and Mandap (1999) simulated the impact of the crisis on nutrition. They found a negative impact of the crisis on macro-nutrient availability. Hence, it is expected that the prevalence of malnutrition will increase because of the crisis.

Looking now at the FGD results, it is the participants’ opinion that in response to the crisis, households have de-prioritized health care. In particular, participants have observed: (1) an increase in malnutrition or a decrease in "nutritional status" among children; (2) a trend of decreasing weight among children; and (3) an increase in illness and a general weakening of resistance and vulnerability to illness. It was also mentioned that parents often leave the children to fend for themselves because of the pressing need to work. There are, however, other participants who pointed out that children are often

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times shielded from adjustments households need to make, particularly, in terms of food intake.

FGD results also mentioned deterioration of health services as one of the key effects of the crisis. One of the primary aspects of this is the absence of medicines that used to be more abundant and free at local health centers. Accordingly, this has rendered these institutions virtually useless except for prescribing pain relievers and referring patients to hospitals that they can ill-afford. In addition, the facilities were said to become even more poorly maintained, feeding programs were suspended and services (e.g., pregnancy tests) were no longer free. Reduction in health personnel and/or their allowances was also mentioned.

The household survey, on the other hand, seems to indicate that health centers continue to be accessible. Only 3% of all households opined that health services have worsened while 26% have reported improvement in the service. More households in poorer communities stated that government health services have improved: 33%, 27% and 26%, respectively, among sustenance farming, fishing, and urban poor communities compared to 18% in middle income communities. In addition, households reported that health workers continue to be available and even increased in some areas. Households, however, agree that the prices of medicines and medical fees have increased. The respondents give an estimate of 20% increase in the price of medicines on the average.

For medical fees, they estimated some 50% increase in hospital and private clinics.

The results of the key informant interviews show that the number of immunized children and pregnant women given tetanus toxoid vaccination did not decline on the average. If there are declines, these were experienced mostly in depressed communities such as upland, sustenance farming, fishing and urban poor communities. The number of health facilities and personnel were mostly not affected. The observation in the FGDs that more people are getting sick is also shared by the key informant interviews although they differ in their assessment of the availability of health facilities and personnel. Finally, the key informant interview confirms the increase in the cost of medicines and medical services.

In terms of nutrition, the key informant interviews show a couple of surprises.

One, the number of malnourished children declined contrary to the impression highlighted in the FGDs. This is true even in urban poor and upland communities although it increased in sustenance farming and fishing communities. This is surprising because one would expect less of malnutrition in essentially food producing areas. Two, the number of barangay scholars supported by the communities increased rather than decreased in all communities. Again, this runs counter to the observations made in the FGDs. To give a broader view of the problems highlighted by the primary data sources, monitoring data using the DOH Field Health Services and Information System (FHSIS) were also gathered for the regions covered by the FGDs to give a broader view of the problems highlighted by the primary data sources. Many of the regions, however, were not able to submit complete data for the whole of 1998. For the immunization program, 6 37

of the 12 regions covered by the FGDs were able to complete their 1998 report. Five of the 6 regions reported a decline in immunization coverage even if 3 of these 5 reported increases in the number of immunized children (Table V.25). This means that the crisis may have affected the ability of the system to respond adequately to increasing demand since some were able to increase the number of children fully immunized but these were insufficient to improve on their previous immunization coverage record. This failure to push forward the immunization coverage might be taken as one of forms of the decline in health services due to the crisis highlighted in the FGDs. For the nutrition program, the FHSIS data for 1998 was complete for 6 of the 12 regions covered by the FGDs. Of these 6, only 2 regions (CAR and Region 7) reported increases in both the number and proportion of moderately and severely malnourished among children 6-59 months old (Table V.26). This corroborates the results of the household survey and key informant interviews and does not support the common impression given in the FGDs that malnutrition among children has increased.

The effects of the crisis on family planning practices were not discussed in the FGDs nor these were covered in the key informant interviews or household surveys. The only information source that can give indications as to what happened to family planning practices during the crisis are the National Demographic Surveys (NDS) done by the National Statistics Office (NSO) and Macro International in 1993 and 1998 and the Family Planning Surveys (FPS) done by NSO in 1996 and 1997. From Table V.27, it appears that there is declining trend in contraceptive prevalence rate (CPR) from 1996 to 1998. It is therefore difficult to attribute the decline in CPR between 1997 to 1998 t o the crisis. However, it is clear from the table that while the overall CPR is declining from 1996 to 1998, the proportion using modern methods was rising up to 1997 before it declined in 1998. On the other hand, while the proportion of those using traditional methods was declining between 1996 and 1997 it increased in 1998. In terms of locality, while the CPR in urban areas is stable at around 50%, the one for rural areas has a mild decline between 1996 and 1997 but had a sharp decline between 1997 to 1998. With the qualifying note that some of the differences may be due to methodological differences of the two surveys, these information point to two possible impact of the crisis. One, the crisis has prevented households from using modern methods of contraception10. Two, there is a drastic decline in contraceptive use in rural areas.

For the family planning program, the FHSIS data for 1998 was complete for 4 of the 12 regions covered by the FGD. Of these 4 regions, 3 reported either a decline in current user or new acceptors or both (Table V.28). This generally corroborates the results of the NDS and FPS that shows that contraceptive prevalence rates have declined.

Inspite of conflicting data from the various sources, the effects of the crisis on the health, nutrition and population sector can be summarized as follows: (1) immunization coverage have been adversely affected; (2) even if household eating pattern have been affected, this has not resulted in a universal increase in malnutrition rate, particularly 10

The 1998 NDHS says that as much as 26.3% of the respondents get their modern method supplies from private medical sources, notably private hospital/clinic (15.4%) and pharmacy (8.1%).

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among children; (3) the use of modern family planning method has been adversely affected and contraceptive prevalence in rural areas has declined.

3.2

Education

The role of education in development is seldom put in question. It is well-known that education improves both the market and home productivity of individuals.

Investment in education is also critical in poverty alleviation (Behrman 1990). Besides these private benefits, there are also large public benefits (particularly for basic education) in having an educated populace. However, these returns come only over longer time horizons. In times of economic crisis people tend to become more shortsighted and put less weight on those activities whose benefits only accrue after longer periods. This is exemplified by parents asking their children to quit school and help augment sagging family incomes. Not only are households oftentimes shortsighted, policy makers likewise frequently fail to see beyond the short-term.

Several studies have related schooling indicators with variables that are affected by the crisis. For instance, based on regression estimates using aggregate data, Lim (1998) pointed out that enrollment rate in all levels is positively correlated with GNP per capita. In addition, elementary enrollment is positively correlated with real education expenditure of government. Finally, college enrollment is positively correlated with the unemployment rate. The crisis is expected to reduce income per capita and increase unemployment. Therefore, the crisis is expected to reduce enrollment in elementary and secondary levels. The impact on college enrollment, on the other hand, will depend on the relative magnitude of the effect of GNP per capita and unemployment rate. Based on the larger share of elementary and secondary enrollment to total enrollment, Lim (1998) expects that the net effect on human capital accumulation will be negative.

Using household survey data, Alba and Orbeta (1999) also found significant impact, albeit small in magnitude, of income on enrollment rates of children 7-14 years old even among those belonging to the bottom 30 percent of the population. In addition, the study also found that enrollment of this cohort is highly responsive to pupil-teacher ratio that is obviously dependent on government expenditure on education. Using the Alba and Orbeta (1999) model to simulate the impact of the crisis on enrollment, Reyes and Mandap (1999) pointed out that the negative effect of the crisis on income yielded a detrimental effect on school attendance. The study pointed out that this result has been validated by a special survey of schools in Metro Manila by the DECS which revealed an increasing number of students dropping out of school and DSWD’s observation of an increasing number of street children. Of course, this study will later point out that this is not only true for Metro Manila but for the whole country as well, particularly for the secondary level.

Looking now at the results of the focused group discussions (FGDs), participants identified decline in enrollment, higher dropout, increased absenteeism, and decreases in student participation in special school activities as the impact of crisis. Many families were reported to have difficulty coping with increases in tuition fees and other school expenses (school materials, uniforms, food and transportation money). The reasons cited 39

for the increases in absenteeism include: (1) the need for children to help out in farm work to save on labor costs; (2) the need for children to watch over younger siblings while parents were at work; (3) the lack of basic school supplies, and money for allowances, transportation and lodging. The absences were noted to have resulted in poor grades and poor quality education. The attendance on special school activities (i.e., scouting) also declined because it meant additional expenses. Finally, the decline in food and transportation money resulted in skipping of breakfast and sometimes children walking to school. All of these, participants added, have contributed to the decline of children's interest in school.

From the household survey, the proportion of those quitting school because of financial reasons is 60%. This proportion ranged from 45.5% for commercial farm communities to 65.2% for urban poor communities (Table V.29). Those who quit school to get employment range from 4.8% for middle income communities to 13.6% for commercial farm communities. Other reasons such as to help in the farm or to help in household chores where mentioned by less than 10% of the households. Thus, financial difficulties have forced a considerable number of households to ask their children to either quit or postpone schooling.

At the awareness level, the household survey reveals there are more households expecting that enrollment in public school will increase and that of private school will decrease. A considerable proportion of the survey participants also expected that there would be more school dropouts although more than half has no opinion about this issue.

Among the primary reasons cited in the FGDs as the cause of higher dropout is the high out-of-pocket cost. It is noted that substantial proportions of these out-of-pocket expenditures are for transportation costs and school projects. This observation is confirmed by the estimates from a 1995 FAPE survey cited in Maglen and Manasan (1998). The transport costs comprise 16% and 27% of total expenditure per student in private and public secondary schools, respectively. The FGD participants also mentioned that public secondary schools are inaccessible. For instance, it was mentioned that students have to walk as far as 7 kilometers to reach the highway and pay P20 for round trip fare to go to school.

While FGD participants volunteered estimates on the extent of decline in enrollment and dropout, these were deemed less reliable so data on enrollments and dropout11 in the locality were taken via key informant interviews and administrative reports of the city, provincial, regional national offices of the Department of Education, Culture and Sports (DECS).

Key informant interviews covered schools in the locality where the FGDs were conducted. The results of the key informant interviews show that total elementary school enrollment rate increased in all but one community between School Year (SY) 1997 and SY1998. Total elementary enrollment even grew faster than the growth in Grade 1 enrollment (4.7% vs. 3.4%) indicating that households have postponed entrance of 11

Owing to smallness in magnitude, the dropout rates gathered at the school level were deemed less reliable. Hence, these were not included in the discussions.

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children to the school system for better times. Even if there is almost an even growth of boys (3.1%) and girls (3.6%) entering Grade 1, there appears to be higher growth rate of enrollment for boys (6.4%) compared to girls (2.9%) for the total elementary grades.

Declines in enrollment are seen in urban poor communities (-10.0%) as middle income communities show positive enrollment growth (15.4%). In the high school level, the total enrollment rate increased by less than 1% with girl's enrollment even declining by 1.6%.

Again, the localities showing declines in growth of enrollment in secondary schools are the depressed ones such as fishing (-10.6%) and upland (-11.9%) communities.

The 1998 Annual Poverty Indicators Survey asked households about their responses to the crisis. The survey reports that a small proportion (6.9%) of households has taken their children out of school. This proportion is understandably higher for the bottom 40% (7.5%) compared to the upper 60% (6.4%).

Based on an administrative report from the DECS, Table V.30 shows that total enrollment in elementary schools continued to increase by 0.67% between SY 1997-98 to 1998-99. This is clearly lower than the usual growth rate of enrollment that is about the growth in population. Growth in enrollment in Grade 1, however, declined by 3.37% indicating that families have postponed the entrance of their children into the school system corroborating the results in the KIs. This phenomenon is true in all regions except for Region 3. Only total enrollment in public schools has increased with private school enrollment declining in double-digit levels (-10.33%). At the secondary level, Table V.31 shows that the decline in the growth of enrollment is universal. Enrollments declined by 7.9% on the average and declined by over 10% in as many as 5 regions.

There is a larger decline in enrollment in private secondary school compared to public schools. However, considering that enrollment in private secondary schools have been declining since the enactment of Free Secondary Education Act in 1988, it is difficult to attribute all these decline in enrollment in private secondary schools to the financial crisis. Again, the decline in the growth of enrollment in first year high school is larger than the decline in total secondary enrollment. This indicates that household are allowing older children to continue secondary enrollment and postponed the enrollment of the new entrants.

The dropout12 data shows that the crisis may have affected only the public secondary grades (Tables V.31 and V.32). Elementary grade dropout rates declined for both public and privates schools. For secondary level, dropout declined for private school but increased by 15.57% for public secondary schools.

Even if the figures from the different sources don't match, it is clear from the foregoing that the crisis had the following effects: (1) enrollment in elementary school have increased at a lower than usual rate; (2) enrollment in secondary schools have declined; (3) households have allowed older children already in the system to continue while postponing the enrollment of new entrants both at the elementary and secondary levels; (4) the dropout of those already in school was not affected in the elementary and 12

This consist of the proportion of enrolled students who did not continue to finish the school-year they are enrolled in.

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private secondary school but increased in public secondary schools; (5) children are making do with smaller food and transportation money.

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4.

Vulnerable Groups

4.1 Farming communities Farming communities had to absorb the impact of two crises: the Asian financial crisis and the El Ni単o. The farmers largely attributed the significant reduction in the volume of their output to the El Ni単o. Although the upland and rain-dependent farmers were the hardest hit, even irrigated farms were not spared. Many irrigation facilities failed to deliver the water to the farms due to the low level of water supply.

A coconut community like Bogo, Tomas Oppus in Southern Leyte, observed that before the El Ni単o, 150 kilos of copra from 500 nuts is normally produced. Because of El Ni単o, their 500 nuts could only give them 60 to 70 kilos of copra. Thus, they missed the opportunity to benefit from the very attractive copra price of P17 as compared with the P7 a kilo in June 1997.

Among the participating barangays, the crisis had the following effects:

a) There were increases in the prices of farm inputs--fertilizers, pesticides, animal feeds, farm labor and equipment rental.

The FGDs reported that the increase varied from 15% to 100%, with animal feeds and farm labor registering close to 100% increases. The cost of fertilizer during the last year and a half were reported to have increased anywhere between 30% to as much as 60%.

Farmers also observed an increase in transportation costs. Palay farmers from Bantol, Marilog, Davao City noted that because of poor road conditions, hauling a 50kilo sack of palay from the farm to the poblacion, which is less than 10 kilometers away, is costly. The rate is P20 for the transportation plus P10 for labor. To save money, some of these people made their wives and children do the work. Consequently, school-aged children were forced to either absent themselves from classes or completely drop out from school. b) The price increases, coupled with the lack of sufficient capital (raised through savings or credit), led to the decline in the use of farm inputs. This decline in the use of inputs contributed to the decrease agricultural production.

The increase in the costs of farm inputs forced farmers to reduce the use of these inputs in their fields. Some FGD communities even reported farmers who did not apply fertilizer at all. This may be a cause of the significant drop in the agricultural output. In Sorsogon for example, barangays claimed their production was down by 40%. c) Many families chose to temporarily abandon their fishing/farming activities to engage in odd jobs that could provide alternative sources of income, as reported by at least 20% of the upland and sustenance farming communities. d) There was selling of farmlands and assets, although others said this was not widespread.

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In some FGD communities close to urban centers, there was an observed increase in land conversion or sale of farmlands. For example, in Barangay Opol, Malanang, Misamis Oriental, participants expressed their concern over the 1,897 has. of timberland in their barangay which may soon be converted to agricultural land because the lease contract made by the government with the farmers already expired last year. Residents have heard that DENR is planning to award this land to some farmers. They said that once the area is declared alienable and disposable, the ecological balance in the area would most likely be adversely affected. e)

Almost all farmers claimed that they could not sell their produce at good prices.

FGD participants reported that the very unfavorable prices for farmers’ produce further compounded their problems. As is the practice, landowners and/or traders are the ones who dictate the selling prices. The farmers are indebted to them because of their assistance, either in cash or in the form of farm inputs. For this, the farmers’ produce would first be sold to them. The ‘suki’ would already deduct the loans when he pays the farmer. The regional financial crisis further weakened the farmers’ power to dictate prices for their produce.

The government’s decision to import huge volumes of rice and corn has been pointed in many FGDs as the main reason for the very low buying price of palay and corn in 1998. Corn farmers for example, said that before the importation, traders were buying corn for at least P5.30 a kilo. During the last major harvest in September, however, corn was priced at only P4 to P4.50 a kilo. Even some big wholesale buyers in Mindanao stopped purchasing corn altogether. In Davao City, palay prices went down from P6 a kilo in 1997 to P4.30 a kilo in 1998. f)

The regional financial crisis aggravated an already oppressive situation.

Even before the regional financial crisis struck, the odds were already against the farmers. As mentioned, farmers were already locked in an oppressive relationship with landowners and/or dealers. Among the FGD participating barangays, most farmers had less than a hectare to cultivate. Most did not have irrigation facilities. Those who did had to contend with poorly maintained ones, as LGUs struggled to maintain their upkeep.

There was, furthermore, limited access to credit. Farmers lack appropriate credit facilities to support their production activities. g)

Farmers also suffer from poor marketing strategies.

At least 23% of all FGD farming communities said that their main problem in increasing their farm income is either the absence of the market that will absorb their produce or the lack of information on efficient marketing systems. Most farming communities rely solely on their ‘suki’ or traditional traders as their main market.

Twenty five percent of upland communities also added that aside from the lack of market, they also did not have control of it.

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h)

The devolution of agricultural services to the local government did more harm than good to the farmers.

The FGDs noted that as an aftermath of the devolution, a number of mayors appointed some technicians who do not have the expertise and training to perform extension services. Some services provided by the DA before the devolution are no longer extended to the communities. This is especially true in communities perceived by municipal government officials as belonging to a different political affiliation.

4.2 Fishing communities The bigger impact of the financial crisis on fishing communities is in the increase of their input and operating costs. This was exacerbated by the already depleted traditional fishing grounds and the consolidation of resources in favor of the elite in the fishing industry. a) Fisherfolks benefited from better market prices but this was more than offset by higher maintenance costs.

For the positive effect, fisherfolks participating in the FGDs said that with the increase in prices came the increase in the market price for fish. This meant added income for the same level of output they used to get from their traditional fishing grounds. The negative effect however, was that while the price for a kilo of fish may have increased, the cost of maintenance of their fishing vessels and gears also increased. The costs of oil and other intermediate inputs have increased accordingly. Most fishing communities said that the increase in the price of fish could not compensate for the increase in the cost of inputs. b) The higher cost of oil and gasoline prevented fisherfolks from expanding into new fishing grounds.

Fisherfolks could no longer catch the same volume because the fish stock in traditional fishing grounds has been depleted. And, because of the increased cost of oil, they could not venture to new fishing grounds. In San Andres, Bauan, Batangas, fishermen may hear of a possible good catch somewhere. The high cost of gasoline prevents them from rushing off to the area. Instead, they wait and see until there is a real assurance of a good catch. Some complained too, that they could not find fishing grounds with abundant fish supply. Illegal fishing practices like dynamite or cyanide fishing and the use of very fine nets have resulted in the destruction of fish sanctuaries. c) In some cases, the crisis also appears to have contributed to the consolidation of various economic resources at the hands of the elite--endowed, as they are, with the financial capability to maintain such resources in productive use.

Forty percent of small fishpond owners in Barangay Kalanganan, Cotabato City, sold their fishponds to bigger pond owners. With the high prices of labor and fishing inputs brought about by the crisis, small fishpond owners found it impossible to repair 45

fishponds destroyed by floods in 1998--and were consequently forced to sell out to bigger fishpond owners. This widespread selling of ponds virtually altered the pattern of ownership of the means of production within the industry.

4.3

Children and Youth

The efforts of poor families to cope with the crisis had serious effects on the welfare of children and the youth, compromising not only the health, education and overall development of these young individuals, but possibly compromising the country’s “social capital”, the next generation upon which the future of the country depends.

Unhealthy changes in the diet caused malnutrition and weakened resistance among children.

About three-fourths of the depressed FGD communities reported that their children, high school and college, left school either to look after younger siblings while parents worked or to become additional income earners. Young girls would work as salesladies or domestic helpers often in cities like Manila or Cebu. Young men would work as farm hands, or migrate to the cities to look for odd jobs. In the Bicol region, many of these children were recruited as household helpers in Manila and other urban areas. FGD participants expressed apprehension over the physical dangers that such young income-earners were exposed to.

Many FGD groups like in three barangays in Cotabato City expressed concern over the vulnerability of out-of-school-youths to the harmful influences of drugs, drinking and petty gambling.

In the Navotas fishing village and some barangays in Davao City, young girls were lured to prostitution. In some cases, the parents themselves were the ones encouraging their daughters to join the flesh trade because of the attractive income.

FGD participants in Ondol (Bohol) and Navotas also observed the vulnerability of out-of-school-youths to early marriages which in turn increases the number of community members with little or no capacity to provide for their families’ needs.

In Tulay na Lupa, Camarines Norte residents noted that “several years from now, we will see an incoming portion of the population not socially and economically prepared to face the rigors of life.”

4.4

Women

The crisis appears to have reinforced women’s proverbial “multiple burden”-forcing more women to take on, in addition to the role of wife/mother/homemaker, the role of secondary income-earner. They engage in direct selling, ambulant peddling of fish and vegetables, open up sari-sari stores or accept laundry work.

Women are also additionally saddled with the need to stretch meager household budgets, the need to source credit and to find money with which to pay past loans.

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Trying to make both ends meet also puts tremendous strain on husband-wife relationships. Two FGD groups reported cases of domestic violence resulting from fierce disagreements as to whether the wife should work or not.

4.5

Senior Citizens and the Disabled

FGD groups in Benguet-Baguio said that senior citizens and the disabled also suffered during the crisis--as survival needs forced them to work and compete alongside the able-bodied.

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5.

Social Fabric

a)

Many communities remain peaceful‌but for how long?

In general, the FGD groups reported no significant disturbances in the peace and order situation in their respective barangays. However, a few communities, particularly those among the urban poor and fishing villages reported a higher incidence of drugrelated problems and criminality. In the fishing village of Sipac, Navotas for example, some participants said that drug abuse in their community is so prevalent that only one percent of households do not have a member who is either a user or a pusher. They said that shabu could be bought anywhere like candy. It was depressing to note, though, that despite the entire community’s awareness of the evils resulting from this problem, nobody seems to want to offer a solution.

Some reported increases in petty crimes, streetchildren and prostitution. b)

Threat to family cohesiveness

The crisis appears to have helped create an environment that is not conducive to maintaining the cohesion of the family. With parents away due to the demands of survival, children were often left to fend for themselves. FGD participants in Gregorio del Pilar (Sorsogon) echoed the sentiments of many communities when they said that parents were not happy having their older children work in big cities, far from the family.

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VI. RESPONSES TO THE CRISIS AND HOUSEHOLD COPING MECHANISMS 1. Government 1.1 Macro Level On the macro level, the immediate response of the government to the crisis was to stabilize the peso mainly by jacking up interest rates and undertaking measures to discourage currency speculation especially by banks. Having recognized the lessons from the experiences of other Asian countries like Thailand, the government also moved quickly to adopt additional prudential measures to further strengthen the banking system.

It likewise resorted to open market operations to control liquidity growth as a way of easing inflationary pressures.

In response to the drastic reduction in government revenues arising from the crisis, the government as mentioned earlier, imposed mandatory reserves on the all government agencies’ operating budget and a reserve on the IRA shares of the LGUs in early 1998. This was, however, lifted in July 1998 for critical basic health and social services. A partial lifting for the LGUs was also made towards the latter part of 1998.

The current administration has programmed a higher budget deficit for 1999 in an effort to avoid a recession. But to keep domestic interest rates low, the government has started to avail of more foreign borrowings and to float bonds in the international capital market to finance the bigger deficit.

To address the challenge of keeping industrial peace in the midst of the crisis, the DOLE facilitated an agreement among employers and labor to cooperate through the Social Accord for Industrial Harmony and Stability. Under this accord, employers commit to exercise restraint in the lay-off and termination of their employees while labor promises to exercise restraint in going on strike, slowing down work and preventing other forms of work stoppages.

1.2 Employment The macro environment would determine the capability of the economy to generate employment. The loss of jobs was linked to the decrease in demand and consequently, no amount of skills training will be able to generate jobs in the near term. Job creation could have come from government pump-priming activities but the fiscal position of the national and local government units prevented them from doing so.

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Provided employment assistance to displaced workers An enormous number of workers were adversely affected by company closures, labor retrenchment and shorter working hours. Workers who were reported permanently displaced from their jobs reached 76,726 for the year 1998. To address this plight, some initiatives were undertaken by the Department of Labor and Employment (DOLE).

DOLE, through stronger networking of their Regional Offices with Public Employment Service Offices (PESOs) based at the LGUs, the Philippine Economic Zone Authority, and other local placement entities, accommodated more active employmentfacilitation or placement assistance to job seekers to ease the effects of the displacement of workers. As a result, about 342,868 placements of job applicants were recorded in 1998.

This placement assistance was extended to overseas labor markets. Inspite of the financial turmoil in the region, deployment in 1998 managed to reach 755,684 OFWs, an increase of 1% from 1997. Remittances declined to US$1.8 billion in the second semester from US$2.9 billion in the same period of 1997.

DOLE had allotted the amount of P7.4 million for the Mindanao regions financing the Rural Works Program for displaced workers in coordination with the Local Government Units (LGUs). This project will fund small infrastructure projects in order to induce employment opportunities in selected depressed, rural communities of Mindanao, particularly for workers displaced by company closures and retrenchments, and those affected by El Niño and La Niña phenomena. A total of 3,364 unemployed workers in Mindanao were able to find temporary jobs in various government infrastructure projects for which P4.4 million of the total budget had already been disbursed. Among them, 1,549 were employed in P2 million worth of various infrastructure projects in CARAGA region, particularly in Agusan del Norte and Surigao del Sur. Another 665 workers were given work in the Central Mindanao provinces of North Cotabato and Sultan Kudarat as well as Lanao del Norte. Moreover, 602 workers found jobs in three infrastructure projects in Davao del Sur. These projects include rehabilitation or maintenance of farm roads, improvement of drainage systems, bridge and solar dryer construction, and the repair and repainting of public buildings.

The government will release another P2.8 million under the Rural Works Program that will benefit some 2,500 workers in Mindanao. It will now be expanded to cover Luzon and the Visayas regions.

Along this line, the CARAGA region developed “Program to Address the Displacement of Employees in the Region” (PADER) to obstruct job loss among those workers who are under threat of displacement and to provide work opportunities among the displaced workers. To date, 20 rural projects were implemented benefiting 957displaced workers.

Likewise, an emergency loan package of P100 Million was approved specifically for displaced sugar workers. In addition, rice subsidies and cash bonuses and other 50

regular benefits received under the Social Amelioration Program were provided. Already 15,384 sacks of rice worth P10 million have been fully disbursed to 76,923 sugar workers and their families from August to November 1998.

In CARAGA region, a pilot-tested Emergency Employment Measures such as training-cum-production and livelihood development adopted the ‘one-village, oneproduct’ concept. The Sinai, Sibagat, and Agusan del Sur areas were developed into an Abaca Village Enterprise, and the Del Pilar, Cagdiamao, Surigao del Norter areas into a Fish Processing Village Enterprise.

Strengthened Job Facilitation Services The Phil JobNet, launched by President Estrada on November 6, 1998 in Malacañang, is a computerized system which facilitates job vacancy and applicantmatching, aiming to help fleetingly job-seekers’ search for jobs and employers’ search for manpower, either for local or international employment. To date, Phil JobNet is being operationalized in five regions including NCR, IV, III, VI and XI, 17 PESOs, 20 Employers Confederation of the Philippines (ECOP) groups, 3 labor federations, PEZA and Malacañang. Accurate information regarding employment opportunities are available and can be easily accessed by employers’ groups, different workers’ organizations and the public.

Provided Welfare Assistance and Benefits for the OFWs Through the established One-Stop Sea-based/Land-based Documentation Center, DOLE streamlined the procedure for processing the documents of the departing OFWs resulting in the reduction of the processing time from five days to just within 24 hours.

In line with this, a One-Stop Balik-Manggagawa Processing Center was also established to streamline the processing of documents of OFWs on vacation during the holiday season. Moreover, an express lane was placed at the Ninoy Aquino International Airport (NAIA) in July for Balikbayan workers in order to facilitate faster processing of Overseas Employment Certificates (OECs).

The Department also operationalized the Re-placement and Monitoring Center, a promotion house for Filipino migrant workers for their local employment to utilize their skills and potentials for the good of the country. Likewise, the DOLE provided a mechanism for their reintegration into the society.

Maintained Industrial Peace The DOLE, through the National Coalition Mediation Board (NCMB), exerted consultative and conciliatory efforts to further minimize the outbreak of labor disputes.

The DOLE facilitated the agreement among employers and labor to cooperate through the Social Accord for Industrial Harmony and Stability. Under this accord, employers commit to exercise restraint in the lay-off and termination of their employees while labor promises to exercise restraint in going on strike, slowing down work and preventing other forms of work stoppages. Through these efforts, the actual number of strikes went down to 23 since July 1998 as compared to 43 cases during the same period of 1997. From 51

July to November 1998, work stoppages affected only 15,898 workers, lower than 23,354 workers affected in the same period of the previous year.

Responses of the Local Governments Some local governments tried to address the rising unemployment. Their fiscal positions, however, severely constrained their capabilities to do so.

The Officer-in Charge of the Provincial Planning and Development Office of Misamis Oriental mentioned that the province adopted the Community Employment and Development Program (CEDP) to generate jobs. This decision was partly due to the fact that the governor in 1997 and some other officials were involved in the CEDP when it was first implemented in the region in 1986-1987. According to Mr. Gallego, this strategy of using more-labor-intensive techniques was adopted during the latter part of 1997 and the whole of 1998 in implementing infrastructure programs under the 20% Annual Development Fund. For instance, in constructing a road, workers will be used instead of graders or compaction equipment. The effectiveness of this strategy in 19971998 would still have to be assessed, however.

1.3 Safety Nets In line with its objective of establishing social safety nets to cushion the poor from economic adversities, the government carried out various measures consisting of food and health care assistance to vulnerable groups affected by the crisis as well as the drought. These include the setting up of sari-sari stores that would sell basic food commodities at lower prices, continuation of the program on the comprehensive and integrated delivery of social services (CIDSS) to address the unmet needs of the poor, the selling of rice at discounted prices by the National Food Authority rolling stores in targeted poor municipalities, and other forms of emergency assistance.

Specifically, the following programs were undertaken: Enhanced Retail Access for the Poor (ERAP) Sari Sari Store and Rolling Store The idea of a rice rolling store was conceptualized based on the premise of providing low cost rice to the remote areas in the country. This was pilot-tested in the rural areas of South and Central Mindanao in July 1988. Upon receiving wide acceptance from the public, the NFA then extended the program to ERAP Sari Sari stores which accredits existing barangay stores to sell basic food commodities at a lower market price. The program also aims to enhance entrepreneurial capabilities and generate employment in the depressed and/or remote areas of the country.

During the previous administration, the NFA has already started a similar kind of program. However, due to the effects of the Asian crisis and the thrust of the Estrada administration relenting to the plight of the poor, the NFA formally launched the ERAP Sari-Sari store as a pro-poor program in a three-pronged approach: availability, accessibility and affordability.

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The sari-sari store caters to the household needs of basic commodities like sugar, coffee, cooking oil, milk, sardines and noodles. The commodities are customized according to the demand of the consumers such as brands, size and packaging. Tag pricing is based on the prevailing market rate of the commodity but the ERAP sari sari store ensures a lower market price.

NFA targets to establish one Erap sari-sari store (ES3) in each of the barangays.

As of January 27 1999, there are already 1,231 Erap stores in the country. The location of the stores considers easy access of the consumers, specifically in the depressed and remote barangays. Interested owners of existing sari-sari stores are enjoined for accreditation. However, if no store wishes to assist in the product delivery, then the NFA or LGUs choose the depot of the Erap commodities.

Rice Subsidy Program (RSP) The Rice Subsidy program was one of the initial steps taken by the government as early as January 1998 to combat the combined effects of the economic crisis and the then upcoming El Niño phenomenon. The main objective of the program is to provide affordable and quality rice to the subsistence poor or else defined as those families living below the food threshold. Priority is also given to those families with at least five members and with moderately and severely malnourished children. Target areas are the identified CIDSS areas which are also highly vulnerable to El Niño. Pilot testing was conducted in these areas for three months after which the full implementation of the program officially started on April 1998.

Phase I. The recipient provinces are Sorsogon, Antique, Iloilo and Surigao del Norte. Three municipalities for each of these provinces are identified. Existing rice retailer stores such as Tindahang Bigay Buhay SEAK Association, NFA retailer stores and other cooperative stores are identified by MSWDO and CIDSS workers as rice retailers for the RSP. The beneficiaries are given rice discount cards which will be used in purchasing rice. The cards are non-transferable to other families and can be used only by immediate members of the family. Subsidy shall be at P2.50 per kilo regardless of the variation in the prevailing price of rice (i.e. If the NFA rice is sold at P14.00 or P13.50, the card holders can avail of the same quality rice with a P2.50 discount).

Phase II (Enriched Rice for Anemia Protection – ERAP). The second phase of the program focused on the distribution of iron- fortified rice. The mechanics used in Phase I was also employed. However, due to budgetary constraints phase II focused only on Surigao and Sorsogon as the baseline provinces. The identification of Surigao as one of the target provinces was due to the significant degree of iron deficiency registered in that province. The subsidy was estimated at P2.54 – P1.50 for the rice subsidy and P1.04 for iron fortification subsidy.

Credit and Livelihood programs DSWD-CIDSS. Some communities were recipients of the DSWD-CIDSS selfemployment assistance program. For example, in Dulong, Libertad, Misamis Oriental,

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CIDSS provided financial assistance to the housewives for their livelihood programs. A seed capital of P200,000 was given to the community. The community was divided into 2 groups called the Strugglers and the Strivers. Each group has 25 members. Each member was given a capital of P4,000 which could be used for any livelihood project – selling fish or vegetables, putting up a sari-sari store, assisting their husbands in the farm operations, etc. The money was to be paid back in installment without interest for 2 years.

To increase the repayment rate, both groups required their members to make daily repayments of P84. Half of the amount is credited as the member’s forced savings. The money is deposited in the bank and the group expects to return the seed capital to the DSWD after 2 years. The community is optimistic that once they learn the value of paying and saving, they would be able to sustain the program when the DSWD pulls out.

The program beneficiaries are appreciative of this DSWD effort as they are able to help augment family income. It was however noted that the DSWD’s requirement of depositing the daily collection in the bank instead of immediately rolling it over to other members of the community, will slow down the community’s effort to evolve a sustainable livelihood credit facility. (It was estimated that through a process of daily amortization roll over, the group could get an additional beneficiary of the P4,000 loan every 2 days).

Social Security Benefits The present system does not provide unemployment benefits. Nevertheless, several measures were adopted by the Social Security System (SSS) to enable members to secure loans as well as to ease the burden of repayment of loans.

Relaxation of qualifying conditions for salary loans. A more relaxed term in availing of salary loans enables SSS members to have easy access to the loan programs.

Effective September 1, 1998 members who have paid at least 36 monthly contributions will qualify for a one-month salary loan. Moreover, the interest rate was reduced from 10% to 6%, with the interest charge incorporated in amortization payments and not deducted in advance.

Employees’ Compensation Emergency Loan Program for separated members.

To compensate the number of unemployed persons in the private sector due to the financial crisis, SSS also designed an emergency loan program for separated members.

Under this loan facility, the members may avail of emergency loans of up to P 12,500 at six per cent annual interest rate, free of service charge. The budget allocation for this loan facility has been increased from P200 million to P 300 million due to the influx of loan applications. A total of 21,219 workers have been assisted, with over P230 million being incurred as loan grants.

Condonation of penalties for housing loan delinquencies. In accordance with the Housing Loan Condonation Act of 1998, SSS condoned penalties of overdue housing loans running from May 8, 1998 to May 9, 1999. To qualify for the amnesty, the borrowers are required to pay their arrears and restructure their loans to prevent foreclosure proceedings against them. At the end of 1998, SSS had P34 million 54

condoned penalties and total collections of P291.3 million with 17,600 members availing the program.

Condonation of penalties for salary, educational, and calamity loan delinquencies. This loan facility follows the procedure in the abovementioned condonation of penalties for housing loan. However, the availment period is from September 1, 1998 to March 31, 1999. As of 30 October 1998, a total of P5 million has been collected from over 1,830 members who have availed of the program.

2. Business The business sector had been adversely affected by the crisis mainly through weaker demand for their products and through higher costs of doing business arising from higher interest rates and import costs. These meant reduced utilization of capacity for many manufacturing firms as indicated in the results of the Survey of Philippine Industry and the Asian Financial Crisis undertaken in late 1998 (Lamberte and Yap, 1999). Based on the survey, many manufacturing firms resorted to cutting down of work hours or days to minimize job losses while some implemented cost-cutting measures like freezing of salary increases, imposing forced vacation, enforcing compressed work week, and for a small number of firms, implementing salary cuts.

In the same vein, FGD participants said that many employers initiated cost-cutting measures to prevent massive lay-off of workers. These include job rotation, longer working hours without additional pay, hiring of workers on a contractual basis and employment of women at below minimum wage.

Almost all firms hire contractual workers, so claimed 57% of the urban poor communities participating in the FGDs. Job security could no longer be enjoyed because of this practice. Under the contracting scheme, employees are hired for a maximum of five months and then are dismissed from the job. (This is to get around the government ruling that hiring of workers on a contractual basis should be only for a maximum of 6 months, otherwise, the worker should be hired on a permanent basis.) Some firms would rehire them after a month but others would opt to take a fresh batch every time the job contract lapses. Rather than be jobless, people were left with no other alternative but to accept the arrangement.

Fifty seven percent of urban poor communities work longer hours with varying compensation arrangements (Table V.13). This is most prevalent in the service industry, particularly that of security guard agencies. For example, instead of hiring 3 security guards to work in 3 shifts, the agencies would ask the guards to work for 12 hours with compensation computed on a per hour basis. Most firms however, would require their workers to work longer hours (usually extending 8-hours a day to 10 to 12 hours) without added pay.

A number of workers have experienced job rotation: 31% of total respondents from middle income (communities); 25% in fishing (communities); and 14% in urban poor communities. Instead of working for 5 or 6 days a week, their working days were

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cut anywhere from 3 to 4 days, with corresponding compensation deductions (Table V.13).

About 15% of the FGD communities reported some firms engaging the services of women workers at lower than minimum wage. In Sipac, Navotas, an urban fishing village, a big fish-processing factory in a nearby barangay employ women as fish sorters at P88 a day. Many accept the arrangement instead of being idle at home.

In April 1999, the Linis Bayan program was launched to provide immediate casual jobs while simultaneously inculcating the daily need for cleanliness in one’s house and surroundings. Linis Bayan encourages participation of the private sector as initiated by the government to create jobs, lessen criminality, improve the sanitation condition, clean the environment, and boost tourism. Private firms which are generating profits will be asked to hire, on a casual basis and on a minimum wage, one or two additional workers to be involved in the Linis Bayan campaign.

3. Households 3.1 Labor In general, workers affected by the crisis took two major courses of action: getting into government jobs perceived to provide them with a more stable employment, or strike on their own through formal and informal business ventures.

A big shift in favor of government work is noted in farming communities. Before the crisis, only 4% of the respondents were in government. At the time of the survey, close to 12% are already working in government offices. Increases of about 4 percentage points were also observed for those who entered household operated activities, transport and utility industries, and factories. (Table VI.1).

Government and factory workers from fishing communities surged from zero during the pre-crisis period to 9% of the respondents after the crisis. An increase of 18 percentage points in the number of employed persons was also noted in the informal sector. Similarly, those engaged in business and personal service increased from 9% to 36%. (Table VI.2).

In the sample urban poor communities, before the crisis nobody worked in government offices. Today, 18% of the employed labor force have government jobs.

There was also a 12 percentage point increase in business and personal service industries and a 6 percentage point addition to the informal sector. (Table VI.2).

Affected workers in the middle income communities took entrepreneurship as a survival route. Table VI.2 shows that there was a large 22 percentage point increase in the number of persons engaged in household-operated activities. Others moved to community service and the business and personal service industries.

FGD participants claimed those businesses like motor shops, appliance repairing, and personal services (beauty and barbershops), felt a slump in business operations. Some 56

entrepreneurs who used to operate in town or in business centers were forced to close shop because of the escalation in the rent, the increase in transport and other operating costs. Some decided to conduct their businesses in their residences to cut down on overhead costs.

About 25% of all household survey respondents cited the desire to change work as the major reason for job shifting. Twenty percent cited the search for better pay and stability in job. Fifteen percent said that they changed work because they were either retrenched, dismissed or the factory or place where they used to work closed shop.

Twelve percent said that their change of residence triggered the change of work. On the other hand, 10% said that the irregularity of their former work compelled them to look for other jobs (Table VI.3).

The FGD participants agreed that among all households, families of overseas workers were the principal beneficiaries of the financial crisis. Except for 3 OFWs who lost their job in Malaysia, the OFWs continue to work abroad. Those who came home did so because of the completion of their job contracts. However, most of them would be traveling again soon. These OFWs work either as seamen, domestic helpers or ‘japayukis’ (a term used for Filipino entertainers in Japan).

Only a few of the migrant workers were directly adversely affected by the financial crisis. Forty three percent of migrant workers who returned to the country in the past 18 months did so because of the completion of their contracts. Nine percent returned because of termination or retrenchment. Of this, about 22% from the urban poor and 17% from the commercial farm communities returned because they said they were dissatisfied with the working conditions. At least 30% of returning migrant workers from the upland, sustenance farm and fishing communities were in the country on vacation and would again be going back to work (Tables VI.4 and VI.5).

Households with relatives working elsewhere are provided with big monetary support. About 28% of these households derive at least 50% of their income from their relatives’ remittances. Another 26% get anywhere from 25-50% of their income from these remittances. In the upland communities, some 38% of the households with relatives abroad said that at least 75% of their income regularly come from the ‘padala’ of these relatives (Table VI.6).

The remittances of these OFWs remained constant. FGD participants noted, however, remarkable improvements in the lifestyles of these households owing to the peso devaluation. Extra money is usually spent for the home, either for the renovation of their current residences or for the purchase of new ones. The OFWs’ spouses were jokingly said to be afflicted with ‘hepatitis’, referring to the sometimes excessive gold jewelry worn. It has also been observed that while most households had problems in supporting the children’s education, the families of OFWs even sent their children to better known schools in the area. In many instances, these families started their own small businesses. Some invested their money in real estate.

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These families are also active initiators for community development. They contribute money to support community projects. Some provide credit facilities for placement fees for those interested to work abroad.

Even with the increased placement fees charged by recruiters, the material benefits available to OFWs continue to attract many people, especially among urban poor communities. However, 43% of the urban poor communities agree that many OFW families are experiencing deteriorated relations and changed values and most often can be seen in their children’s attitudes. The lack of proper guidance from both parents often results in the child’s disinterest in school. Most of them would rather hang-out with their ‘barkada’ (peer group). Many children tend to be materialistic. Others turn to vices like smoking, gambling and even drug use. For the married couples, adulterous relations of one or both spouses were reported to be common (Table VI.7).

The increase in prices of consumer goods, and--in the case of farming/fishing families-- the increase in the prices of farm/fishing inputs, combined with low harvests and fish yield, and low selling prices, forced families to look for other sources of income.

A few decided to return to the province either to work in the farm, engage in fishing activities or simply live with their relatives, so claimed FGD participants. Some residents of 25% of the fishing communities sought employment elsewhere.

The crisis appears to have nourished the growth of the underground economy.

Forty six percent of the middle income and 43% of the urban poor communities engaged in selling fish, putting up a sari-sari store, or direct selling. The stability and viability of the sector as a source of income, however, can at best be described as questionable. Many went bankrupt after only a few months of operations, apparently because they lacked the business know-how (Table VI.8).

In Lumil, San Jose Batangas, FGD participants opined that finding a job in their community is not really a problem. According to them, there are many livestock and poultry farms in the barangay in need of farm hands. The local job-seekers however, frown on such menial jobs. As a result, these farms get laborers from other provinces (mostly Bicolanos).

3.2 Household Expenditures The FGD participants reported various ways in which people coped with the crisis, particularly with the increase in prices of consumer items and other basic necessities. Some of the coping mechanisms include reduction and reallocation of expenditures, borrowing, and selling of assets to compensate for reduced income.

FGD participants, however, reported that “coping” has taken its toll. As a result of unhealthy changes in food consumption, malnutrition has increased among children.

Illness results from weak resistance, which in turn comes from poor nutrition. The 58

education of children has also suffered--as the number of school drop-outs has increased due to out-of pocket expenses incurred even by those in public schools.

1.

Household budget was adjusted (Table VI.9)

As a result of the financial crisis, household respondents to the survey were forced to make some adjustments in their budget. The table below shows the allocation of income vis-Ă -vis the major expense items before the crisis and at present.

Expense item Food Education Medical/Health Clothing Transportation Housing Leisure

1997 46.3% 10.0 7.9 7.0 7.2 5.0 2.8

1998 47.3% 10.3 8.1 5.9 7.3 5.2 2.1

The adjustments reflect the priority level attached to a specific item of expenditure. Food received the largest upward adjustment to catch up with the price increases of basic food items such as meat, vegetables, cooking oil sugar and other processed food items. Households also made upward adjustments in education, medical/health, transportation and housing expenses. They had to sacrifice clothing and leisure in the process.

Inspite of the bigger allocation for food, households still had to adopt some changes in their food consumption patterns. Many households did away with nonessentials such as softdrinks, ice cream, meat, coffee, etc. Others resorted to having only one viand per meal, and generally, less of meat and more of the cheaper food items such as dried fish and vegetables. Some resorted to backyard food production to augment food supply.

Apparently because of poor harvest and unattractive prices for agricultural products, upland farm communities had to make the largest adjustment in food budget.

Respondents from these areas reported 4% increases. Fishing and middle-income communities made a 2% increase. Sustenance farm and urban poor households managed to keep their budget. Commercial farming communities had a 2% decrease.

To cope with the increased cost of schooling, majority of households in all communities increased the allocation for education. Sustenance farm communities made the largest adjustment of 0.6%. Fishing and upland communities had 0.5%. Commercial farm communities made a 0.2% adjustment. Urban poor and middle income households registered the lowest adjustment of 0.1%.

The surge in medicine and medical fee costs also resulted in budget changes.

Middle income households effected a 0.6% increase. Urban poor communities made a 0.5% increment. Upland and fishing communities made 0.4% upward adjustment. Two communities reduced their budget for medical expenses. Commercial farm community 59

households scaled down their budget by 1%. Sustenance farm community households on the other hand, managed to shave off 0.4%.

For housing, four communities (urban poor, middle income, upland and fishing) made upward adjustments from 0.1% in urban poor communities to 0.4% in middle income communities. Commercial farm households kept the pre-crisis proportion of housing expenditure, while sustenance farm communities reduced their budget by 0.4%.

Increased transportation budget was largest among households in middle income communities at 0.7%. Fishing, upland and sustenance farm households effected increments not exceeding 0.4%. Decreases were 0.6% for commercial farm and 0.4% for urban poor communities. The larger allocation to transportation was noted inspite of efforts to reduce transportation expenses. People resorted to more walking instead of riding vehicles; riding jeepneys instead of tricycles and taxis; segregating errands that entail transportation expenses; and requesting neighbors going into town to buy whatever is needed (“pakisuyo�).

All households reported reducing their clothing budget from 0.4% in middle income communities to 1.6% in urban poor communities. Second-hand clothes were bought instead of new ones and use of hand-me-downs were resorted to. Ready-to-wear clothes were bought instead of having a custom-made dress. School children either had to use the old uniform or buy just one set.

Budget for leisure was significantly reduced in urban poor (1.6%) and fishing (1.5%) communities. Households from middle income and sustenance farm communities likewise made a 1.2% reduction.

2.

Credit provided additional household resource

Uses of credit (Tables VI.10 and VI.11). Credit was used more for consumption than for productive purposes during the crisis. Although people continued to avail of credit facilities for consumption purposes and to raise capital for income generating projects, consumption loans increased relative to business loans because people had less money to spend for basic needs.

Those who availed of credit used the additional resources for a variety of reasons.

Thirty two percent used the money to augment their household income. Twenty seven percent was meant to support the school expenses of children; 21% went to pay for medical expenses of sick household member(s); 19% used the money to buy household capital goods (mostly appliances); 16% had to repair their houses; another 16% used the money to support the household productive activities. At least 30% of borrowers from the farming communities used the credit principally to support farm production.

It is apparent from the pattern of utilization of credit that at least 84% of the credit obtained by the households (except for farming communities) were not used for productive purposes. This means that they would have to pay back the money they

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borrowed from their regular sources of income. Thus, it would not be surprising if many of these households would later incur arrears for non-payment of loans.

The amount of credit availed is a clear indication of the financial difficulties brought by the current crisis. Forty four percent of those who availed of credit said that they borrowed more than what they used to borrow before the onset of the crisis. About 20% claimed to have borrowed up to 10% more than before. Sixty eight percent were equally divided on the amount of loan they got after the onset of the crisis. One half said that they exceeded their pre-crisis credit ceiling by up to 25%; the other half exceeded it by up to 50%. Meanwhile, 11% said that they borrowed over 50% of the credit level they were getting before the crisis.

Sources of credit. Sixty-three percent of the households availed of credit during the past 18 months prior to the survey, relying more on informal lenders. According to the household survey, 46% of households relied on relative and friends to get loans, 24% on “5/6” lenders, and 26% on banks. The Indian nationals, locally called ‘bumbays’ are one of the more popular sources of “5/6” loans. Four percent get loans from traders.

Many farmers go to traders for production loans because interest rates are negotiable. A little over 10% got loans from unmentioned sources. Farming communities named their friends/relatives and banks as the two most ready sources of credit (Table VI.10).

Formal lending institutions’ credit facilities became more inaccessible. To the majority of the FGD participants, their primary consideration in approaching a potential credit provider is the ease in acquiring a loan. As a result of the crisis, formal lending institutions were reported to have become more inaccessible because of stricter lending guidelines, increased collateral requirements and voluminous paper work. Very few residents went to the banks for small loans as they were overwhelmed with the many requirements they were to submit and the many papers they had to sign. It was therefore not surprising that the informal credit providers were their preferred source.

Banks, cooperatives, pawnshops and GFIs (GSIS, SSS or Pagibig) are the most common sources of formal credit. Government and private employees can avail of the GSIS, SSS or Pagibig loans.

Banks and pawnshops normally have collateral requirements. The amount of loan that could be had from cooperatives is usually a fraction of the member’s total savings in the coop.

Informal moneylenders provided less credit facilities. Credit facilities provided by informal moneylenders remained available, but to a less extent than before the crisis.

The same usurious rates of at least 20% per month continued to be utilized by informal money lenders. These moneylenders, however, became more choosy and wary because of what they perceived as the diminished paying capacity of borrowers.

Among the informal moneylenders, the traders and “bumbays” dominate.

FGDs reported a proliferation of informal credit sources in some areas because of the increased demand for quick credit. From Luzon to Mindanao, the same groups of individuals have been identified as the most popular sources of credit. These are the traders, private individuals and the ‘bumbay’ (Indian nationals who usually ride in 61

motorcycles and provide commodity and cash loans). The same usurious interest rates of anywhere from 10% a month to 20% a week continued. Loans are usually paid either on a daily or weekly basis. Loans provided by traders to farmers, for instance, are settled on harvest time when the farmers sell their outputs to them.

These moneylenders, however, became more choosy and wary because of what they perceived as the diminished paying capacity of borrowers. Barangay officials attested to this condition. They said that many credit providers complain about delinquent borrowers. For this reason, some creditors chose not to lend at all.

3.

When credit was not accessible or available, people resorted to selling assets to raise cash

To cope with their financial woes, about 17% of households surveyed reported to have sold some assets in the last 18 months. About 20% of them sold real property, specifically land. Of this, 33% came from middle income communities. Appliances (18%) and jewelry (18%) were the two other properties often sold. Only about 3% sold their houses, most of them from fishing communities. In farming communities, 77% sold animals such as carabao, cattle, hogs and goats, while 43% of the urban poor sold their jewelry. (Tables VI.12 and VI.13).

The most compelling reason cited for the disposition of properties was to augment household income (52%). Additional reasons include: payment of school fees (11%), payment of health service including medicine (8%), and payment for loan (4%). Only 3% claimed to have sold some asset to provide capital for productive activities (Table VI.12).

The sale of assets could lead to a more inequitable distribution of wealth. Past gains in land reform could be undermined by this recent turn of events.

3.3 Health, Nutrition, and Population Government has not introduced special measures to counteract the impact of the crisis on health, nutrition and population sector beyond exempting it, along with other social services, from the mandatory reserve of 25% of the 1998 budget and 10% cut in the Internal Revenue Allotment for Local Government Units.

The FGD gathered information on the household coping mechanisms. There was a general tendency to de-prioritize health in household budgeting. The other coping schemes include reliance on free or cheaper sources of health services such as government facilities, traditional healers, self-medication, seeking assistance from barangay officials and politicians, NGOs operating in the area and prayers. Health care from private practitioners or hospitalization had become a luxury. However, as mentioned earlier, the lack of medicines has often hindered access to public health care facilities.

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The 1998 Annual Poverty Indicators Survey asked households about their response to the crisis. The survey revealed that 47% have altered their eating pattern. This proportion is higher for the bottom 40% (51.4%) compared to the upper 60% (45.5%).

As to the effect of this adjustment on nutrition however, no indication was given.

It is also interesting to note that a study of the impact the 1983-84 economic crisis on urban poor communities in Cebu and Davao, found similar household coping mechanisms including among others, reduced consumption expenditures notably food and limitation of additional children (Herrin 1987).

3.4 Education Just like the health sector, government has not introduced special measures to counteract the impact of the crisis on education beyond exempting the sector, along with other social services, from the mandatory reserve of 25% of the 1998 budget and 10% cut in the Internal Revenue Allotment for Local Government Units.

The FGDs have gathered information on how households and communities cope with the crisis. One of the saving grace for education mentioned is that government subsidized elementary and secondary education. There are also sporadic scholarships from NGOs which students have availed of to be able to stay in school.

Feeding programs, although in limited quantities, have also helped particularly those children who have gone to school with lesser allowance. Since most of these are funded from government revenues, these may have been further limited due to the crisis.

Families, for their part, resorted to several cost-minimizing steps just to keep their kids in school. These include: (1) letting their children stay in public schools; (2) transferring their children from private to public schools; (3) asking younger children to postpone schooling to allow children about to finish a cycle finish expecting that they can, in turn, help their younger ones to go back to school; (4) sacrificing basic necessities like sugar to save for tuition; (5) setting school allowance to minimum levels or letting children go to school without allowance and supplies; (6) letting children go to class without uniforms or with untidy clothes to save on soap; and (7) asking children to walk to school to save on transportation expenses.

Working part-time for students who can is also another coping mechanism used.

Students tended stores, worked as sales ladies or house help, or sell bottles and plastic bags.

4. Community A few barangays have instituted measures to preserve peace in the area and prevent the youth from engaging in unlawful activities. The responses mentioned were holding regular consultative assemblies, instituting curfews for teenagers, and confidential monitoring of movements of people, especially non-residents. There are also

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civic-minded individuals who took the initiative to organize the out-of-school youths and give them regular training or lectures on value formation and spirituality.

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VII.

ASSESSMENT OF EXISTING MONITORING SYSTEMS

Eighteen months have elapsed since the onset of the crisis and it is still not widely known what the social impacts are. While we have monthly data on prices and international reserves, we have data on poverty incidence every three years and prevalence of malnutrition every five years. The absence of an adequate monitoring system makes it difficult to assess the impact of macroeconomic crises and natural calamities. This also hampers the design and implementation of targeted interventions to alleviate the adverse impacts of the crises.

This is primarily because social indicators, unlike economic indicators, are generally fewer and collected infrequently. Moreover, some data are available at the local level but they take a very long time, if ever they do so, to go up to the national level to make them useful to national policymakers. On the other hand, some indicators are too aggregated to provide useful information for targeting interventions.

Assessment There are recent attempts of the government to develop monitoring systems, especially related to poverty. While there are systems for collecting data, it is obvious that there is really no existing system for collecting, processing and disseminating data on a regular basis that would enable policymakers and program implementors to monitor and evaluate the programs being implemented to enhance social development in a comprehensive and regular manner.

1.1 National Monitoring System There is no single monitoring system at the national level that tracks the performance of the country vis-Ă -vis the different aspects of social development. There are different sources of data on the different dimensions of welfare. Administrative reports of different government agencies, and surveys and censuses undertaken by the Philippine Statistical System, particularly the National Statistics Office, are the major sources of data.

For instance, data on infant mortality rate can be obtained from the vital statistics records of the National Statistics Office and the National Demographic and Health Survey. The former provides annual estimates but they are considered to be understated since not everybody reports births and deaths. The NDHS, on the other hand, is conducted only every five years.

Enrolment rates can be obtained from the administrative reports of the Department of Education, Culture and Sports. It takes about a year, however, before the data from the various school districts could be aggregated to generate regional and national estimates.

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At the central offices of the line agencies, provincial and regional data are available but municipal and barangay data may have to be collected from the provincial municipal offices, respectively.

Table VII.1 shows the different items of information related to the well-being of the population that could be obtained from these various sources.

While sectoral assessments may be done yearly by the different government agencies in the course of the preparation of their annual reports, a comprehensive assessment of the performance of the country vis-Ă -vis the various social concerns is undertaken when a development plan is made or updated. Since a new development plan is prepared every six years and it is updated mid-period, an assessment is done every three years.

More recently, our international commitments to achieve social development targets necessitate a regular though not annual review of our accomplishments in the social area. In this regard, the United Nations Economic and Social Council for Asia and the Pacific (UN ESCAP)is considering the setting up of a social development monitoring and information system. In an ESCAP meeting, it was noted that such a monitoring system is not existing right now in these countries. In the case of the Philippines, Reyes (1998) claims it is feasible to develop a system given the existing data collection activities.

1.2

Community-based monitoring system

Recognizing the deficiencies of the existing statistical system, there has been a lot of interest in developing community-based monitoring system (CBMS) recently. The CBMS would be very useful in monitoring what is happening to the different population subgroups. Moreover, it would provide the necessary information for more efficient targeting.

MIMAP The Micro Impacts of Macroeconomic Projects has proposed a community based monitoring system in 1992. The details are presented in the paper of Florentino and Pedro (1992) and modified in the paper of Reyes and Alba (1994). A set of indicators has been identified and a flow of information has been designed.

CIDSS The Department of Social Welfare and Development has implemented the Comprehensive and Integrated Delivery of Social Services in 1994. Part of this program is a community-based monitoring system using the MBN indicators. This is intended to meet the information needs of the social workers to identify appropriate interventions to the family. But as early as 1990, the Social Welfare Development Indicators has been developed to identify the needs of families.

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PCFP The Presidential Commission to Fight Poverty viewed the community-based information system as an empowerment tool for the community. It started to conduct this in 1996. By June 1998, when PCFP has been merged into the newly created National Anti-Poverty Commission, about 20,000 barangays13 have conducted at least one round of the community-based census of households.

In the meantime that changes in the organizational structure of the NAPC are being effected, no one has taken the lead in monitoring the conduct of said CBIS. Visits to selected barangays by the study team reveal that many have not undertaken the survey every six months as originally designed. In fact, for some of the barangays, the first and last survey was done in 1996.

Despite the data collection that has been done by many communities under the supervision of PCFP, the data have not been consolidated to reach policymakers at the provincial and national levels.

The proposed Poverty Watch that will enable policymakers to know the status of the communities vis-Ă -vis the minimum basic needs still has to be implemented.

Recommendation The lack of an adequate monitoring system can hamper the ability of the various stakeholders to respond appropriately to adverse impacts of a macroeconomic crisis. It is therefore imperative for the government to establish a social monitoring system that will enable policymakers, the researchers and the general public to assess the welfare status of the individuals and households, and to provide early warning signals on the adverse impact of a crisis.

The proposed social monitoring system will obtain its data from the following: (1) administrative reports being collected by the various agencies of the national government and local government units; (2) censuses and surveys being undertaken by the National Statistics Office; and (3) community-based monitoring system.

Since the data will be coming from different sources, it will be important that a focal agency be designated for this social monitoring system. Moreover, an annual report should be prepared and presented to policymakers and the public on the performance of the country in the social sectors, similar to the regular briefings done on the economic performance of the country.

As proposed by MIMAP14, a monitoring system calls for the creation of databanks at each geopolitical level. Data on relevant indicators will be retrieved periodically from concerned line agencies and the information will be fed to the development planning bodies at the respective levels. The databank could be the Barangay Development Council (or a Barangay Development Planning Office) at the 13 14

Accoridng to PCFP. Refer to papers of Florentino and Pedro (1992) and Reyes and Alba (1994).

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barangay level, and the Municipal/City and Provincial Development Planning Offices at the municipal, city and provincial levels. The National Statistics Office may then obtain MIMAP statistics from these databanks for reporting to national level policymakers.

Alternatively, the national monitoring system could be lodged at the National Statistical Coordination Board, the National Economic and Development Authority, or the Philippine Institute for Development Studies.

The community-based information system developed and implemented by the Presidential Commission to Fight Poverty (now part of the National Anti-Poverty Commission) could be revived and modified and be a crucial component of this social monitoring system. The concern regarding the quality of the data being collected in the CBIS could be addressed by modifying certain features of the current CBIS. For example, the experience of MIMAP suggests that it would be better to use the barangay Health Worker and the Mother Leaders as the enumerators. Moreover, data on malnutrition should be obtained from the records of the barangay Health Worker and not rely on the recall of the respondents in the household survey. Furthermore, reliable data on income is very difficult to obtain from such a data collection activity. Instead, proxy indicators for income should be used in this system.

To ensure that barangays will continue with the conduct of the survey, this should be made a part of the barangay planning process as proposed by Reyes and Alba (1994).

In Davao City, the study team found that it is a requirement to conduct the MBN survey first before the barangay development plan is approved. However, it was found also that the same survey conducted in 1996 could be used repeatedly. Local government units could adopt the same strategy to ensure that the programs being proposed by the barangays are based on the unmet needs of the barangay. The Department of Interior and Local Governments can also strengthen the planning capabilities of the barangays by incorporating the use of the data from the CBMS in their training modules for local officials.

The Annual Poverty Indicators Survey (APIS) undertaken by the National Statistics Office could provide the data provided by the triennial Family Income and Expenditure Survey in between the conduct of the FIES. The APIS could provide the required data on family income.

With a social monitoring system in place, particularly with the community-based monitoring system, the targeting scheme being employed by the government in its poverty alleviation projects can be further improved. During the Ramos Administration, 20 provinces were selected as priority areas for the implementation of the Social Reform Agenda. This was further refined to 5th and 6th class municipalities nationwide. More recently, the President has announced that poverty alleviation efforts will be focused on the poorest 100 families in each province and city nationwide. The community-based monitoring system will be very useful in identifying the poorest families in each locality.

With clear guidelines on eligibility to government assistance programs, identification of beneficiaries could be done by local governments.

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VIII. CONCLUSION AND RECOMMENDATIONS It is clear that the financial and economic crisis, together with the El NiĂąo and La NiĂąa, has affected the vulnerable groups via reduced employment and higher prices which resulted in lower real incomes. This in turn forced affected households to cope by attempting to look for other income opportunities and to make adjustments in their spending and consumption patterns. Because of financial difficulties faced by households, their need for public social services increased. Unfortunately, because of the fiscal crunch, social services especially in health suffered.

The sectors most affected by the financial crisis are the construction, manufacturing, and mining and quarrying sectors. The agricultural sector was also adversely affected but this is considered to be more a result of the abnormal weather rather than the crisis itself. The services sectors were relatively protected although in the case of financial services, it began feeling the crunch as early as 1997.

Both the urban and rural communities were negatively affected by the crisis. In the urban areas, the impact was more pronounced among the poor. In the rural areas, farmers and fisherfolks were more badly hit. Self-rated poverty deteriorated the most among fishing and upland communities and among the urban poor. This is consistent with the findings in terms of where there are experiences of lower enrolment rates and higher drop out incidence.

The middle income households seem to have been relatively less affected by the crisis. In middle-income households adversely affected by the crisis, the reasons given are job retrenchments and reduced number of earning family members. Among workers, the first to lose their jobs are the less educated and less skilled or younger persons.

For those who lost their jobs because of the crisis, an attempt is made to look for other income earning opportunities in the informal sector or in government, or to hit it on their own doing entrepreneurial activities. Others had to contend with doing odd jobs.

Women coming from families whose male workers were laid off were also forced to look for income earning opportunities.

The most common household coping mechanism in response to the crisis is adjusting one’s buying and consumption patterns. Priority was given to food needs, with non-essentials like clothing and leisure being the first to be given up. Expenses such as those for education and transportation were increased to accommodate higher prices.

However, health care was de-prioritized. Reduced enrolment growth and higher dropout incidence also indicated that some households pulled out their children from school or postponed their schooling, especially for those entering either the elementary or secondary levels for the first time.

On the whole, the social impact of the crisis in the Philippines does not appear to be very serious by itself and relative to the crisis-related experiences in Indonesia and Thailand as initially reported. The policy reforms instituted in the years prior to the crisis seems to have been timely and have contributed to the greater resiliency of the economy 69

to the crisis. Compared to the impact of the debt crisis in the early 80’s, the impact of the present crisis also seems much more manageable.

This, however, does not offer much of a comfort considering that prior to the crisis, the Philippines was way behind the other ASEAN countries in both economic and human development aspects. On the human development side, the country’s welfare situation is already very serious to begin with and any further slippage, no matter how small is not acceptable.

On the fiscal side, it is unfortunate that the provision of basic social services is curtailed when it is most needed. Worse, access to the services by persons or families who need it most is not assured by the present social service delivery system. This problem is reinforced by the absence of a strong monitoring system that would identify the individuals and groups that should be targeted.

There are two ways of addressing this problem. First, by making available the necessary resources to reach the identified families or individuals when the situation calls for it. Second, by ensuring a more effective allocation and utilization of resources through better targeting mechanisms and more effective projects with immediate or significant impacts.

On the first point, the analysis indicates that although the social service sectors were protected relative to other sectors from the fiscal crunch, the shortfall in government revenues is of such magnitude as to effectively reduce the budget cover for all sectors and, consequently, the coverage of basic social services. Undoubtedly, there is a need for additional sources of deficit finance if this problem is to be addressed. Domestic borrowing, however, carries the risk of raising local interest rates which may then stifle nascent recovery efforts. Thus, there is a need for government to look at external sources of finance. In this light, external assistance from donor agencies in the form of budget support is called for.

A number of donor agencies are in the process of providing budget support to the government. Given this perspective, such budget support may be made conditional on government commitment: (1) to increase resources allotted to the social service sectors, and (2) to rationalize the allocation of resources within the social service sectors.

On the second point, a targeting mechanism that is more community-based and further brought down to the barangay level should be pursued. This is along the same line as the devolution strategy but further brought closer to the targeted beneficiaries themselves. The barangay level is deemed to be the most appropriate focal point for identifying the potential beneficiaries, determining their needs, and delivering the required social services. The minimum basic needs (MBN) approach adopted by the former Presidential Commission to Fight Poverty (PCFP), which promotes participatory planning at the community level, can be used as a take off point. The program can be strengthened and fully supported. This will also necessarily imply the need to undertake the necessary institutional building capability at the community level.

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To support a community-based targeting mechanism and to provide a timely and adequate response to a crisis, a strong social monitoring system has also to be established and maintained. Following the assessment in the previous chapter, the following are the main recommendations towards the establishment of such a monitoring system: 1) Obtain and integrate existing information from various sources (administrative reports, official statistics, censuses and surveys) at the national and community level 2) Create appropriate data banks at each geopolitical level 3) Revive and strengthen the community-based information system developed by the PCFP 4) Integrate the community-based monitoring system with the local planning process 5) Designate a focal agency to be responsible for the coordination and maintenance of the social monitoring system and for the reporting of performance based on the results under the monitoring system.

In addition to the general recommendation of ensuring better availability of resources and adopting a community-based targeting mechanism as one of the measures to improve resource allocation, the specific issues in the different areas of concern arising from the crisis will have to be individually addressed.

The specific recommendations along this line are discussed below.

1. Access to Basic Commodities An impact of the crisis that was widely felt was the increase in prices. To help the poor meet their basic requirements, programs that enhance access to basic commodities will be necessary in times of crisis. Making such commodities available in areas where they are usually scarce at lower than market prices is critical. For instance, the ERAP stores mentioned in Section 1.3 enabled households to buy basic commodities at prices slightly lower than market prices. The National Food Authority was able to do this through bulk buying and its marketing network.

It is important to emphasize, however, that the proposed program does not intend to promote price control as this will run counter to the government’s market-oriented policy and to its efforts at reducing the budget deficit. The proposed program should be target-specific and should not be made to apply indiscriminately to families and individuals.

2. Employment Short-term. The immediate and short-term response to the negative effects of the crisis on employment will necessarily have to include the implementation of pumppriming projects especially in the more affected geographic areas. These can include rural infrastructure projects which are beneficial to the development of these communities and which can improve their long-term productivity. The use of more labor-intensive techniques particularly in infrastructure projects, both in the short and 71

long term should also be promoted. Along this line, the Community Employment and Development Program can be adopted not just as a crisis measure but as a regular feature of the employment strategy.

Structural. While the crisis and the El Niño adversely affected employment, even without the crisis, unemployment and underemployment are already high especially in the rural areas. This is because much of the underlying causes of high unemployment are structural in nature. Although short-term measures are proposed, the structural problems have to be addressed over the medium and long term. The solution to this concern can be tied up with the implementation of the government’s agriculture and fishery modernization program and the strategy to address the inherent weaknesses in the manufacturing sector (such as low productivity and level of technological development).

Plans to fully implement the agriculture modernization program which is supposed to be in place in 1999 (although there are still funding constraints to be addressed) should be supported. In general, the proposed strategies attempt to address both the absorptive capacity and the low level of productivity in the sector. Moreover, to minimize fluctuations in income due to the vagaries of weather, rural non-farm employment need to be promoted.

To enable women to avail of employment opportunities, day care services should be made available the whole day from the current 2-3 hours a day.

Another concern that has to be addressed is the workers’ skills. To better equip workers with skills that will enable them to compete in a global environment, reforms in the educational system are necessary. Skills training programs need to be more marketled rather than supply-driven. This means that the type of skills to be promoted are those needed by the market.

Similarly, livelihood programs have to be market-led too. For instance, it is possible that there can be too many meat processing ventures. There can be a large production volume but the marketing side is neglected. This is an often-cited problem.

Either the individual does not have adequate knowledge as to where and how to market his product or there is no demand for the product. This highlights the importance of taking the marketing aspects in consideration when providing livelihood programs.

3. Credit The popularity of informal lenders, particularly the “bumbays”, as sources of credit among the cash-strapped households stems from the ease in acquiring the loan and the repayment scheme. Unlike with formal lenders, there is usually little or no collateral required and there is very little or no paperwork involved in applying for a loan. This feature becomes even more important during the crisis when the collateral base especially of farmers usually collapse.

On the aspect of repayment, the amortization is usually on a daily basis, which perfectly matches the income stream of the usual borrowers such as those engaged in retail trade (sari-sari store operators, market vendors, etc.), and the daily-paid workers 72

(construction, drivers, laundry women). In the case of farmers, traders are popular sources, again both because of the “no-collateral� requirement and because of the repayment scheme. Farmers are able to pay their loans at harvest time. Thus, traders are only too willing to lend because they can accept the produce as payment.

Credit programs for the poor should therefore take two important considerations: the collateral aspect along with the need for simple procedures, and the cash flow of the borrowers. Borrowers from poor communities inherently lack the capability to show collateral. Moreover, in general, they are mostly more comfortable in repaying on a daily basis as many of them (except the farmers) earn their income on a daily basis. Thus, credit programs that match the collateral base and cash flow of borrowers should be promoted. Grameen-type programs in providing the poor access to credit should be encouraged.

Banks cannot handle this type of operation but NGO-type organizations can be tapped as they are better equipped for this. In fact, there had been recent cases of banks using NGOs as a conduit for their loan programs.

4. Health, Nutrition and Population Structural. In terms of allocation of health resources, the government should continue to focus on the provision of primary and public health care services rather than be drawn into curative care as the current trend is showing. This focus is being eroded by the heightened support to retained hospitals due to the perceived breakdown of the devolved district hospitals. Not only is this tendency undermining the devolution, it is also drawing limited public health resources into areas where government should have limited presence. On the other hand, the social insurance based financing for access to curative care should be pushed. The Philippine Health Insurance Corporation must be supported to improve its coverage of indigents as well as improve its fund utilization.

Stronger and more consistent support for family planning programs and more human capital investment opportunities for women are needed to pull down the high population growth rate of the country. This will not only make the economy grow faster but it will also make the provision of services less burdensome to the families and the economy as a whole.

Short-term. With the decline in immunization coverage due to the crisis, there is a need to provide special support for this program to restore coverage levels. This is particularly so because the shots need to be administered at specific periods in a child’s life.

Households respond to drastic changes in prices even for food. While households were, in general, able to protect their children from malnutrition, this will easily be threatened by increases in prices. There is then a need to stabilize prices, particularly of food, so as to enable households to continue to protect the nutrition status of their members. Even if malnutrition has not increased in general, pockets of increases in

73

malnutrition incidence were observed. There is therefore a need to expand well-targeted feeding programs particularly because there is a very limited number of such programs.

The decline in contraceptive prevalence, particularly the modern methods, needs to be arrested. The country’s population is growing at a rate faster than its Southeast Asian neighbors. The country’s contraceptive prevalence is also one of the lowest in the region. There is therefore a need to increase funding for contraceptive supplies to arrest this decline in contraceptive prevalence.

5. Education Structural.

Education resources are being dissipated unnecessarily by maintaining too many underutilized state colleges and universities. Support is needed to rationalize government investments in education. Rationalizing government investments in tertiary education, which promotes leadership in specific fields and improve access of the poor through other means besides public provision, should be pursued. In basic education, cost recovery schemes in areas such as textbooks need to be considered.

To improve upon the 1:6 pupil-to-textbook ratio in elementary and 1:8 ratio in the secondary level, several options are available. Textbooks can be allocated in a pro-active manner utilizing cross-subsidy. Children of better-off families can be made to pay for their textbooks so as to allow more children of poor families to have free textbooks.

Another way is to reduce the number of textbooks from the current 10 to say 4 covering only the core subjects.

There is a need to arrest the decline in school attendance. One significant factor is high out-of-pocket cost. A major proportion of this out-of-pocket cost is transportation primarily because of the distance from homes to the school. The current unwritten objective of “elementary school in every barangay and a high school in every municipality” may not be attainable in the foreseeable future. There are even doubts on the cost-effectiveness of this way of providing basic education. Efforts at choosing other cost-effective options need to be supported. One, providing bus services may be effective in areas where there are good roads. Two, providing dormitory housing for students from far-flung areas may be a better alternative for areas where roads will not make bus services feasible. Three, in areas where schools can be cost-effectively provided, incentives for teachers to locate in these areas need to be developed.

Short-term. The current government subsidy to basic education through the Education Service Contracting (ESC) and Tuition Fee Supplements (TFS) components of Government Assistance to Students and Teachers in Private Education (GASTPE) can be so designed to counteract the dropout and withdrawal of students in the secondary and elementary schools. Since this is expected to be high in poor households, the subsidy should be targeted to them. In order for this to happen, targeting the poor is necessary but not sufficient. Increasing the support value of the subsidy is needed so that the poor will be encouraged to avail of it. Covering some of the out-of-pocket cost may even be necessary.

74

REFERENCES Alba, M. and A. Orbeta (1999). “A Probit Model of School Attendance for Children 7 to 14 Years Old,” MIMAP Research Paper.

Behrman, J. (1990). “The Action of Human Resources and Poverty on One Another,” LSMS Working Paper No. 74.

Florentino, Rodolfo F. and Ma. Regina A. Pedro (1992). “Monitoring the Micro Impact of Macroeconomic Adjustment Policies (MIMAP),” Working Paper Series No. 92-19.

Herrin, A. (1987). “Economic and Demographic Adjustments to Economic Stress: The Case of the Urban Poor,” processed.

Lamberte, Mario B. and Cesar Cororaton, et al. (1999). “Results of the Survey of the Philippine Industry and the Financial Crisis,” PIDS Research Paper.

Lim, Joseph. (1998). "The Social Impact of and Responses to the Current East Asian Economic and Financial Crisis: The Philippine Case," UNDP, Manila.

Maglen, L. and R. Manasan (1998). “Education Finance in the Philippines,” ADB/IBRD Philippine Education Study.

Orbeta, A. and M, Alba (1999). "Macroeconomic Policy Change and Household Health Outcomes: A Simulation of the Impact of the 1990-2000 Tariff Reform Program on the Demand for Outpatient Care in the Philippines," MIMAP Research Paper.

Orbeta, A. and M. Alba (1998). "Simulating the Impact of Macroeconomic Policy Changes on Macronutrient Availability in Households," MIMAP Research Paper.

Reyes, Celia M. (1998). “The Social Impact of the Regional Financial Crisis in the Philippines,” MIMAP Research Paper.

Reyes, C. and E. del Valle (1998). “Poverty Alleviation and Equity Promotion,” PIDS Research Paper.

Reyes, C. and B. Mandap (1999). "The Social Impact of the Regional Financial Crisis in the Philippines," MIMAP Research Paper.

“Social Impact of the Financial Crisis in Asia: Economic Framework,” ADB Headquarters, Manila, 1998.

75

TABLE I.1 EXCHANGE RATES FOR SOUTHEAST ASIAN COUNTRIES, 1997-1998 Year

Month

1997

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

1998

Indonesia Malaysia Singapore Thailand Philippines Korea (Rupiah/US$) (Ringgits/US$) S$/US$ Baht/US$ PhP/ US$ Won/US$ 2396 2406 2419 2433 2440 2450 2599 3035 3275 3670 3648 4650 10375 8750 8325 7970 10525 14900 13000 11075 10700 7550 7300 8025

Sources: Bank of Indonesia Bank of Malaysia Monetary Authority of Singapore Bank of Thailand

2.49 2.48 2.48 2.51 2.51 2.52 2.64 2.96 3.20 3.44 3.50 3.89 4.55 3.68 3.64 3.74 3.88 4.18 4.14 4.22 3.80 3.80 3.80 3.80

1.41 1.42 1.44 1.44 1.44 1.43 1.45 1.50 1.52 1.56 1.58 1.65 1.75 1.66 1.62 1.60 1.64 1.70 1.71 2.87 2.90 2.78 2.72 2.76

25.71 25.93 25.95 26.05 25.87 25.78 30.27 32.48 36.28 37.55 39.30 45.29 53.71 46.30 41.33 39.48 39.14 42.36 41.19 41.58 40.41 38.14 36.41 36.19

26.3 26.3 26.3 26.4 26.4 26.4 27.7 29.3 32.4 34.5 34.5 37.2 42.7 40.4 39 38.4 39.3 40.4 41.8 43 43.8 42.9 39.9 39.1

849.88 866.85 879.41 893.56 892.05 889.49 890.50 895.90 909.53 921.85 1024.58 1484.08 1701.53 1626.75 1488.87 1388.32 1400.13 1395.26 1293.70 1312.12 1372.58 1336.24 1297.74 1211.50

TABLE I.2 DIRECT AND PORTFOLIO INVESTMENTS, 1990 - 1996 Net Direct Investments US$ M Growth Rate (%) 1990 1991 1992 1993 1994 1995 1996

528 529 675 864 1289 1361 1338

Source: Bangko Sentral ng Pilipinas.

n/a 0.19 27.60 28.00 49.19 5.59 -1.69

Net Portfolio Investments US$ M Growth Rate (%) -48 125 62 -52 269 248 2179

n/a 360.42 -50.40 -183.87 617.31 -7.81 778.63

TABLE I.3 EXTERNAL DEBT AND DEBT SERVICE BURDEN AS PERCENT OF GDP FOR SELECTED EAST ASIAN COUNTRIES, 1990 - 1996 1990

1991

1992 1993

1994

1995

External Debt ( in billion US dollar) Philippines 30.0 31.4 Indonesia 66.9 76.1 Malaysia 15.4 16.1 Thailand 25.1 33.4 Korea 46.8 54.7

32.1 83.8 16.4 37.4 59.2

35.5 89.5 19.2 46.8 66.2

38.7 39.4 58.6 64.4 28.0 33.9 55.0 68.1 85.6 113.5

Debt Service Burden (As % of GDP) Philippines 8.00 6.23 Indonesia 8.71 8.06 Malaysia 9.79 5.67 Thailand 5.07 4.11 Korea 2.32 1.59

5.55 8.30 6.95 4.55 1.87

5.94 8.39 6.71 4.85 2.49

6.54 7.42 8.00 5.01 1.71

Source: Selected Philippine Economic Indicators.

6.79 7.49 6.43 4.33 0.89 .

1996 41.9 59.1 38.9 90.5 112.6 6.07 8.76 7.23 3.55

TABLE II.1 REAL GDP GROWTH RATES IN SELECTED EAST ASIAN COUNTRIES 1990 - 1996 (In Percent)

Indonesia Malaysia Singapore Thailand China Korea Philippines

1990

1991

1992

1993

1994

1995

1996

7.2 9.7 9.0 11.2 11.5 9.5 3.0

-0.8 8.6 7.3 8.6 10.3 9.1 -0.6

6.5 7.8 6.2 8.1 14.2 5.1 0.3

6.5 8.3 10.4 8.7 13.5 5.8 2.1

7.5 9.3 10.5 8.9 12.7 8.6 4.4

8.2 9.4 8.7 8.7 10.5 8.9 4.8

8.0 8.6 7.8 6.4 8.2 7.1 5.8

Sources: International Financial Statistics, National Statistics and Coordination Board.

TABLE II.2 INFLATION, INTEREST RATE, EXCHANGE RATE, 1981-1996

1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

Inflation Rate (%)

91-Day T-bill Rate (%)

Exchange Rate (Peso/US$)

17.8 8.6 5.3 47.1 23.4 -0.4 3.0 8.9 12.2 14.1 18.7 9.0 7.6 9.1 8.1 8.4

n/a n/a 14.2 28.5 26.7 16.1 11.5 14.7 18.6 23.7 21.5 16.0 12.4 12.7 11.8 12.3

7.9 8.5 11.1 16.7 18.6 20.4 20.6 21.1 21.7 24.3 27.5 25.5 27.1 26.4 25.7 26.2

Sources: National Statistics Office, Bangko Sentral ng Pilipinas

TABLE II.3 BALANCE OF PAYMENTS, GROSS INTERNATIONAL RESERVES, EXTERNAL DEBT, 1981 - 1996 Year 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

BOP (US$ M) -547.0 -1671.0 -2118.0 243.0 2301.0 1242.0 264.0 593.0 451.0 -93.0 2103.0 1492.0 -166.0 1802.0 631.0 4107.0

Source: Bangko Sentral ng Pilipinas.

GIR (US$ B) 2.6 1.7 0.9 0.9 1.1 2.5 2.0 2.1 2.3 2.0 4.5 5.2 5.8 7.0 7.6 11.6

External Debt (US$ B) 20.9 24.7 24.8 25.4 26.3 28.3 28.6 27.9 27.6 30.0 31.4 32.1 35.5 38.7 39.4 41.9

TABLE II.4 GROSS NATIONAL INCOME PER CAPITA, 1960 - 1994 ( In Constant 1987 US dollars ) Country Indonesia Malaysia Singapore Thailand Korea, Republic of China Philippines Source: World Data 1995, CD.

1960

1965

140 810

140 860

320 330 70 430

400 390 60 450

1970

1975

1980

1985

1990

1994

160 210 340 950 1,130 1,740 4,090 5,370 530 590 740 610 850 1,840 90 100 140 510 570 660

410 1,840 7,460 830 2,530 210 540

480 2,260 10,550 1,270 4,200 270 630

570 2,940 15,010 1,620 5,320 410 640

TABLE II.5 UNEMPLOYMENT RATES OF SELECTED ASIAN COUNTRIES, 1971 - 1995 Country Indonesia Malaysia Thailand Singapore Korea Taipei, China Philippines

1971

1975

1980

1985

1990

1995

...

6.8 ...

4.8 4.5 ...

4.8

...

6.9 0.4 4.6 4.1 ...

4.2

1.7 5.6 0.9 3.5 5.2 1.2 5

2.1 6.9 3.7 4.1 4 2.9 7.1

2.5 5.1 2.2 2 2.4 1.7 8.1

1.6a 2.8 1.5b 2.7 2 1.8 8.4

Notes: 1994 b 1993 a

Sources: 1971-1975: Key Indicators of DMCs of ADB, 1985.

1980-1995: Key Indicators of Developing Asian and Pacific Countries, ADB, 1996.

TABLE II.6 POVERTY IN SELECTED ASIAN COUNTRIES, SUMMARY STATISTICS, 1975-1995

Economy

China Indonesia Malaysia Philippines Thailand Vietnam

Head-count Index (percent) 75 85 59.5a 64.3 17.4 35.7 8.1 n.a.

37.9 32.2 10.8 32.4 10.0 74.0b

95 22.2 11.4 4.3 25.5 <1.0 42.2

Notes: All numbers in this table are based on the international proverty line of US$1 per person person per day at 1985 prices a.: Data relates to 1978 and applies to rural China only. b.: The figures refer to 1984. "Vietnam Household Welfare in Vietnam’s Transition" in Macroeconomic Reform and Poverty Reduction, edited by D. Dollar, J. Litvack, and P. Glewwe. World Bank Regional and Sectoral Study, 1998 n.a.: not available Source: Everyone’s Miracle?, World Bank 1997.

TABLE II.7 HUMAN DEVELOPMENT INDICATORS OF SELECTED ASEAN COUNTRIES, 1988-1995 1988

1989

Low-Birth-Weight Infants (%) Indonesia Malaysia Philippines Singapore Thailand

14.0 10.0 18.0 6.0 12.0

-

Crude Death Rate (per 1,000 population) Indonesia Malaysia Philippines Singapore Thailand

11.0 6.0 8.0 6.0 7.0

9.0 5.0 7.0 5.0 7.0

Infant Mortality Rate (per 1,000 livebirths) Indonesia Malaysia Philippines Singapore Thailand

84.0 24.0 44.0 9.0 38.0

73.0 23.0 44.0 8.0 27.0

Access to Health Services (%) Indonesia Malaysia Philippines Singapore Thailand Access to Safe Water (%) Indonesia Malaysia Philippines Singapore Thailand

1990

1991

14.0 10.0 15.0 7.0 13.0

1992 1993 1994 1995

-

-

-

8.9 5.3 7.4 5.4 6.8

9.0 5.0 7.0 5.0 6.0

8.4 5.1 7.0 5.7 6.1

8.3 5.1 6.9 5.8 6.1

71.0 22.0 43.0 8.0 26.0

68.0 15.0 42.0 7.0 28.0

58.0 13.0 44.0 6.0 37.0

-

14.0 8.0 15.0 7.0 13.0

-

8.0 5.0 6.8 4.8 6.1

-

53.0 12.0 55.0 5.0 29.0

-

/1

-

-

-

80 90 75 100 70

-

-

-

-

51 72 82 100 76

-

-

-

44 94 69 96 74

80 76 100 90

-

76 100 90

-

51 78 82 100 77

-

62 78 85 100 86

-

44 94 69 99 74

-

51 94 69 99 74

-

80 -

/2

Access to Sanitary Toilet (%) Indonesia Malaysia Philippines Singapore Thailand

/2

NOTES : - data not available /1 figures for the year are the average of the period starting 1985 /2 figures for the year are the average of the period starting 1988 figures in italics are from the World Development Report Sources: UNDP Human Development Report, World Bank, Asian Development Bank Annual Report.

Pe rC ap i U ne ta G m D p P Ea loym (P PP rn en in ), tR gs U Ad at S p e ul er (% $ c tL on em ) ite st M p r an a ea lo c y t y n e R e Ye a Li te ar fe s (% of Ex Sc ) pe Lo ho ct w an ol Bi in cy rth g a C t W ru Bi ei de rth de ght In In at fa fa h nt nt ra s M te (% or Ac (p ta ) e ce l r i ty 1, ss R 00 to at Ac 0 e H ce po r ( a p ss pu lth er la to 1, Se Ac t 0 Sa ce rv 00 ion ) ic fe ss liv es W to eb ( a % Sa te irt O ) r( hs VE ni % t ) ar R ) y -A To LL ile R t( O A % VE N ) K R I N -A G LL R A N K IN G

TABLE II.8 HUMAN DEVELOPMENT RANKING OF SELECTED ASEAN COUNTRIES, 1988-1995

Indonesia Malaysia Philippines Singapore Thailand 4 2 5 1 3 1 3 4 2 3 4 1 2 4 5 1 3 2 3 2 1 4 5 5 2 4 1 3 4 2 5 1 3 5 2 4 1 3 4 2 5 1 3 4 3 1 2

5 4 3 1 2 5 2 4 1 3

Sources of basic data: UNDP Human Development Report, World Bank, Asian Development Bank Annual Report.

3.9 2.7 3.3 1.6 2.9 5 2 4 1 3

TABLE III.1 GDP and SECTORAL GROWTH TRENDS, 1990-1998 (Growth Rates in Percent) 1990-1993 1994-1996 Gross Domestic Product Agriculture, Fishery and Forestry of which: Palay Corn Coconut including copra Sugarcane Other crops Livestock Poultry Industry Sector Mining and Quarrying Manufacturing Construction Electricity, Gas and Water Service Sector Source: National Statistics Coordination Board.

1.2 6.1 0.0 2.9 -0.6 8.4 0.6 2.5 7.7 0.3 0.5 -2.2 -0.6 2.0 2.1

4.9 2.2

Q1 5.5 4.9

Q2 5.6 1.8

1997 Q3 4.9 0.4

Q4 Year Q1 4.8 4.1

Q2

1998 Q3 Q4 Year

5.2 1.6 -0.8 -0.7 -1.9 -0.5 2.9 -3.8 -11.5 -3.1 -7.8 -6.6

6.3 1.6 -6.0 -15.5 9.9 -0.1 -4.6 -2.0 11.7 6.9 1.4 4.4 2.2 8.3 9.5 9.5 -3.2 5.7 -1.2 7.9 -15.0 -85.8 17.3 0.4 2.9 9.1 2.5 9.9 4.0 6.2 5.5 5.6 6.6 4.5 4.8 5.3 6.4 11.1 7.2 0.6 8.0 6.8 5.3 5.1 7.6 6.4 5.6 6.1 -6.4 -13.1 -1.0 1.8 23.9 1.7 5.8 2.3 5.3 4.3 4.7 4.2 8.8 21.3 18.5 18.1 7.6 16.2 11.4 3.8 8.0 4.1 3.4 4.8 5.1 6.1 5.7 5.6 4.6 5.5

-13.4 -23.5 -1.8 9.7 -6.3 2.2 4.6 1.6 17.5 2.0 -5.0 7.2 4.5

-41.4 -68.7 -14.4 -31.9 -4.5 3.6 1.4 -0.2 5.7 -0.9 -1.8 6.1 3.6

-28.2 13.8 -15.0 -83.8 -6.8 4.3 -2.9 -3.4 1.9 -1.5 -15.6 3.2 2.7

-19.9 8.3 -19.0 -39.0 -5.9 6.2 -4.0 -4.4 -16.0 -3.4 -10.0 1.5 3.3

-24.1 -11.7 -13.1 -13.8 -5.8 4.1 -0.3 -1.8 1.4 -1.1 -8.1 4.4 3.5

TABLE III.2 GNP by EXPENDITURE SHARES, 1990-1998 (Growth Rates in Percent) 1990-19931994-1996 Personal Consumption Expenditure Government Consumption Capital Formation Exports Goods Non-Factor Services Imports Goods Non-Factor Services Gross National Product Source: National Statistics Coordination Board.

3.5 2.5 3.6 4.7 5.2 3.8 7.3 7.5 6.1 2.2

Q1

Q2

3.7 5.0 5.1 6.1 0.4 3.3 8.7 14.9 7.1 19.8 22.3 17.2 13.4 8.6 15.2 29.4 51.0 21.0 14.5 13.90 9.8 15.2 3.0 2.7 35.6 190.7 73.5 5.3 5.4 5.3

1997 Q3 Q4 Annual Q1 5.0 2.6 9.3 13.4 17.6 7.0 17.3 10.2 77.3 5.2

4.9 -0.2 15.0 18.3 14.5 24.3 16.3 15.0 24.3 5.3

5.0 1.6 11.7 17.5 14.2 23.4 14.4 7.8 71.8 5.3

4.5 -1.4 -9.2 11.4 13.4 8.6 4.0 -2.3 40.2 2.0

Q2 3.9 1.5 -16.0 -10.3 3.7 -36.2 -13.9 -12.1 -23.4 -0.3

1998 Q3 Q4 Annual 2.9 1.7 -18.9 -16.3 6.3 -53.9 -14.4 -13.1 -21.3 0.01

2.8 1.4 -23.9 -22.1 -4.8 -47.4 -19.0 -18.6 -20.9 -1.2

3.5 0.8 -17.1 -10.4 4.1 -33.8 -11.4 -11.9 -8.5 0.1

TABLE III.3 UNEMPLOYMENT AND UNDEREMPLOYMENT RATE, 1990 - 1998 (In Percent) 1995 1996 1997 1998 Sem1 Sem2 Sem1 Sem2 Sem1 Sem2 Sem1 Sem2 22.4 22.5 20.5 21.7 21.4 20.0 21.0 22.1 21.8 38.9 41.1 21.6 20.5 22.3 22.0 21.3 22.3 8.4 10.5 9.8 9.3 9.5 9.5 8.5 8.7 10.1 20.9 17.2 9.6 7.5 9.1 8.3 10.9 9.3

1990 1991 1992 1993 1994 1995 1996 1997 1998 Underemployment Rate Unemployment Rate Source: National Statistics Office.

TABLE III.4 IMPORTS BY COMMODITY, 1995-1998

Levels (In Billion US$)

1995 1996 1997 1998

1997 1998 Sem1 Sem2 Sem1 Sem2

1999 Jan - Feb

Total Imports Capital Goods Raw Materials & Intermediate Goods Mineral Fuels & Lubricant Consumer Goods Special Transactions

26.4 31.9 36.4 29.5 8.0 10.5 14.4 12.0 12.2 14.1 14.6 11.6 2.5 3.0 3.1 2.0 2.8 3.3 3.1 2.6 0.9 1.0 1.2 1.2

17.4 6.2 7.5 1.5 1.6 0.5

19.0 8.1 7.2 1.5 1.5 0.7

15.2 6.2 5.6 1.1 1.2 1.1

14.3 5.8 5.5 0.9 1.4 0.6

4.7 1.9 1.8 0.3 0.4 0.2

Growth Rates (In %) Total Imports Capital Goods Raw Materials & Intermediate Goods Mineral Fuels & Lubricant Consumer Goods Special Transactions

23.7 16.9 26.7 20.6 32.0 32.8

11.1 26.2 6.1 10.4 -9.5 5.9

16.9 -12.2 47.1 -0.1 2.1 -24.8 -4.8 -28.4 -4.6 -23.4 26.5 109.7

-25.0 -28.8 -22.9 -40.2 -6.4 -8.1

-12.0 -13.8 -11.9 -33.8 10.1 5.0

20.8 14.0 -18.8 30.4 37.2 -16.1 15.5 4.1 -20.8 22.2 2.2 -34.3 19.6 -7.2 -15.2 7.7 16.8 5.0

Sources: Bangko Sentral ng Pilipinas.

National Statistics Office (for January and February 1999 values).

TABLE III.5 EXPORTS BY COMMODITY, 1995 - 1998 Level (In Billion US$)

1995 1996 1997 1998

Total Exports Manufactures of which: Electronic Eqpt.&Parts Garments TextileYarns/Fabrics OtherAgro-BasedProducts MineralProducts/Petroleum Products SpecialTransactions/Re-Exports

17.4 13.9 7.4 2.6 0.2 2.1 1.1 0.4

Growth Rates (In %) Total Exports Manufactures of which: Electronic Eqpt.&Parts Garments TextileYarns/Fabrics OtherAgro-BasedProducts MineralProducts/Petroleum Products SpecialTransactions/Re-Exports

29.4 17.7 30.6 23.3 48.7 34.7 8.2 -5.7 20.2 21.2 25.5 -12.7 16.7 -2.0 49.4 31.0

Source: Bangko Sentral ng Pilipinas.

20.5 17.1 10.0 2.4 0.3 1.9 1.0 0.5

25.2 21.5 13.0 2.3 0.3 1.9 1.0 0.8

29.5 25.9 17.2 2.4 0.2 1.9 0.7 1.0

22.8 16.9 25.5 20.5 30.4 31.7 -3.1 0.3 18.7 -19.1 4.4 -4.1 -2.2 -29.4 60.5 30.3

1997 1998 1999 Sem1 Sem2 Sem1 Sem2 Jan-Feb 11.7 13.5 13.9 15.6 5.4 9.9 11.5 12.0 13.9 4.6 5.9 7.1 7.9 9.4 3.1 1.1 1.3 1.1 1.2 0.3 0.2 0.1 0.1 0.1 0.0 1.0 1.0 1.0 0.9 0.2 0.5 0.5 0.4 0.3 0.1 0.3 0.5 0.6 0.5 0.5

22.3 23.8 18.6 15.2 25.8 25.4 20.7 20.4 27.3 33.2 32.9 31.5 -6.6 0.2 2.9 -1.8 42.0 0.0 -12.6 -25.6 4.2 -0.9 4.4 -9.1 -4.5 0.0 -25.8 -32.9 37.2 107.9 64.9 -7.4

23.3 23.7 27.1 -3.3 -23.2 -45.8 -15.1 216.3

Table III.6 Balance of Payments In Millions of US$, 1995-1998

Balance of Payments Current Account, Net Trade Goods, Net Exports Imports Services,_Net Transfers, Net Capital and Financial Acccount, Net Medium and Long-Term Loans, Net Availments Repayments Trading of Bonds in the Secondary Market Resale of Bonds Purchase of Bonds Investments, Net Non-Resident Investments in the Phils.

Resident Investments Abroad Short-Term Capital, Net Change in Commercial Banks' NFA Purchase of Collateral Others Net Unclassified Items Source: Bangko Sentral ng Pilipinas.

1995

1996

1997

1998

631 -3297 -4179 -8944 17447 26391 4765 882 3393 1276 3927 2651 . . .

1609 2944 1335 -56 564 .

81 454

4107 -3953 -4542 -11342 20543 31885 6800 589 11072 2841 6540 3699 -37 4148 4185 3517 3621 104 540 4211 .

-5 -3007

-3284 -4351 -5431 -11127 25228 36355 5696 1080 6593 4824 7724 2900 -676 3072 3748 761 842 81 493 1191 .

-360 -5166

1346 1294 859 -28 29496 29524 887 435 956 2850 5791 2941 -1082 3308 4390 1672 2016 344 -1521 -963 .

84 -988

Q1 474 -519 -767 -2893 5506 8399 2126 248 2731 1291 2012 721 -177 943 1120 1000 944 -56 264 353 .

-181 -1557

1997 Q2 Q3 -742 -974 -1652 -1461 -1897 -1762 -2764 -3081 6194 6663 8958 9744 867 1319 245 301 3074 1901 1055 1720 1818 2216 763 496 -167 -139 826 704 993 843 -231 -25 -214 32 17 57 -25 130 2442 215 . .

59 -56 -2223 -1358

Q4 -2042 -719 -1005 -2389 6865 9254 1384 286 -1113 758 1678 920 -193 599 792 17 80 63 124 -1819 .

-182 -28

Q1 617 -85 -272 -1085 6816 7901 813 187 811 689 1071 382 -89 620 709 521 622 101 -589 279 .

53 -162

1998 Q2 Q3 942 22 97 427 -43 347 -253 512 7089 7940 7342 7428 210 -165 140 80 1891 -1294 1699 196 2595 870 896 674 -251 -164 658 1254 909 1418 187 -133 265 -45 78 88 -238 -153 494 -1040 . .

-45 88 -1001 801

Q4 -235 855 827 798 7651 6853 29 28 -452 266 1255 989 -578 776 1354 1097 1174 77 -541 -696 .

-12 -626

FIGURE II.1 REAL GDP GROWTH RATES, 1981-1996 8.00 6.8 6.2

5.8

6.00 4.4

4.3 4.00

3.4

3.6

3.4

3.0 2.1

1.9

2.00

4.8

In Percent

0.3 0.00 1981

1982

1983

1984

1985

1986

1987

1988

1989

1991 -0.6

-2.00

-4.00

-6.00

-8.00

1990

-7.3

-7.3

-10.00 Year Source : National Statistics Coordination Board.

1992

1993

1994

1995

1996

FIGURE II.2 REAL PER CAPITA GNP, 1981 - 1997 14000 12701

12711

12603

12663 12298

12000

11385

11177

11554

11308

10971 10148

10264

1985

1986

11151

11456

1993

1994

11743

11194

10537

In million Pesos

10000

8000

6000

4000

2000

0 1981

1982

1983

1984

1987

1988

1989 Year

Source: National Statistics Coordination Board.

1990

1991

1992

1995

1996

1997

Figure II.3 FISCAL POSITION, 1981 - 1996 20

10

0

In billion Pesos

-10

-20

-30

-40

-50

-60 1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

Year

National Government Cash Operations Source: Bureau of Treasury.

Consolidated Public Sector

FIGURE III.1 MONTHLY EXCHANGE RATES, 1997 - 1999 50

45

Peso per US$

40

35

30

25

20 Jan Feb Mar Apr May Jun 1997

Jul

Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 1998

Month Source: Bangko Sentral ng Pilipinas.

Jul

Aug Sep Oct Nov Dec Jan Feb Mar 1999

FIGURE III.2: MONTHLY 91-DAY TREASURY BILL RATES, 1997 - 1999 21

19

17

In Percent

15

13

11

9

7

5 Jan Feb 1997

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Jan Feb 1998

Month Source: Bangko Sentral ng Pilipinas.

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb 1999

FIGURE III.3 MONTHLY AVERAGE BANK LENDING RATES, 1997 - 1998 22

20

In Percent

18

16

14

12

10 Jan

Feb

Mar

Apr

May Jun

Jul

Aug Sep

Oct

Nov Dec

Jan

1997

1998 Month

Source: Bangko Sentral ng Pilipinas.

Feb

Mar

Apr

May Jun

Jul

Aug Sep

Oct

Nov Dec

FIGURE III.4 INFLATION RATE 12.00

11.00

10.00

Percent

9.00

8.00

7.00

6.00

5.00

4.00 Jan

Feb Mar

Apr

May Jun

1997

Jul

Aug Sep

Oct

Nov Dec

Jan

Feb

1998

Apr May Jun

Jul

Aug Sep

Oct

Nov Dec

Jan 1999

Month Source: National Statistics Office.

Mar

Feb

Mar

FIGURE III.5 TRADE BALANCE, 1990 - 1998 1000

0 1990

1991

1992

1993

1994

In million US$

-1000

-2000

-3000

-4000

-5000

-6000 Year Source: Bangko Sentral ng Pilipinas.

1995

1996

1997

1998

FIGURE III.6 GROSS INTERNATIONAL RESERVES, 1997 - 1999 12.5

12.0

11.5

In Billion US$

11.0

10.5

10.0

9.5

9.0

8.5

8.0 Jan

Feb

Mar

Apr

1997

May Jun

Jul

Aug Sep

Oct

Nov Dec

Jan

Feb

1998 Month

Source: Bangko Sentral ng Pilipinas.

Mar

Apr

May Jun

Jul

Aug Sep

Oct

Nov Dec

Jan 1999

Interest Rates for South East Asian Countries, 1997 - 1998 40

35

30

In Percent

25

20

15

10

5

0 Jan Feb Mar Apr May Jun 1997

Jul

Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 1998

Month

Jul

Aug Sep Oct Nov Dec

Indonesia

Malaysia

Singapore

Thailand

TABLE IV.1 NATIONAL GOVERNMENT REVENUES AS A PROPORTION OF GNP, 1986-1998 (In Percent)

1975-85

1.

2.

Average 1986-91 1992-97

1986

1990

1992

1994

1996

1997

1998

TOTAL REVENUES

12.90

15.97

18.34

13.29

16.71

17.52

19.36

18.26

18.67

16.59

TAX REVENUES

11.26

13.12

15.86

10.98

14.01

15.06

15.62

16.38

16.31

14.94

a. Bureau of Internal Revenue

6.72

8.86

11.04

7.85

9.61

9.66

10.80

11.64

12.44

12.09

b. Bureau of Customs

4.04

4.08

4.70

2.93

4.24

5.26

4.70

4.62

3.77

2.72

c. Other Offices

0.51

0.20

0.13

0.20

0.16

0.14

0.13

0.11

0.11

0.12

1.64

2.84

2.48

2.31

2.70

2.45

3.74

1.88

2.36

1.65

NON-TAX REVENUES

Source of basic data: Bureau of Treasury.

TABLE IV.2 NATIONAL GOVERNMENT DEFICIT AS A PROPORTION OF GNP, 1986-1998 (In Percent)

1975-85

Average 1986-91 1992-97

1986

1990

1992

1994

1996

1997

1998

Revenues

12.90

15.97

18.34

13.29

16.71

17.52

19.36

18.26

18.67

16.59

Expenditures

15.15

18.87

18.34

18.53

20.15

18.67

18.42

17.87

18.61

18.37

SURPLUS/DEFICIT

(2.25)

(2.90)

(0.00)

(5.24)

(3.44)

(1.15)

0.94

0.39

0.06

(1.79)

Source of basic data: Bureau of Treasury.

TABLE IV.3 1997/1998 REVENUE PROGRAM (In Million Pesos) 2/ 1997 BESF 1/ 1997 Deviation 1998 BESF 1998 GOP -IMF 1998 1998 Deviation Program Actual Program Target Target Acutal Target Collection (2)-(1) Target 02/24/1998 06/16/1998 Collection (7)-(4) (1) (2) (3) (4) (5) (6) (7) (8)

1.

TOTAL REVENUES % of GNP

485,110

471,843 18.4%

-13,267

540,920

531,302 19.7%

488,037 17.0%

462,616

-78,304

TAX REVENUES % of GNP

450,595

412,165 16.1%

-38,430

513,088

498,354 18.5%

453,661 15.8%

416,585

-96,503

a. Bureau of Internal Revenue

317,786

314,697

-3,089

389,087

378,688

367,303

337,175

-51,912

b. Bureau of Customs

129,486

94,800

-34,686

121,205

116,918

83,611

76,005

-45,200

2,668

2,668

2,748

2,748

3,405

3,405

59,678

25,163

32,948

34,376

45,930

18,098

c. Other Offices 2.

NON-TAX REVENUES

34,515

Notes : 1/ BESF - Budge of Expenditure and Sources of Finance 2/ GOP - Government of the Philippines Source: Department of Budget and Management

27,832

TABLE IV.4 GROWTH RATE OF NATIONAL GOVERNMENT EXPENDITURES, BY SECTORAL CLASSIFICATION, 1975-1999 (%)

75-85 GRAND TOTAL

AVERAGE 86-92

93-97

1995-96

1996-97

1997-98

1998-99

16.06

19.08

13.48

4.76

17.95

12.59

9.72

Total Economic Services

14.05

8.03

15.12

1.20

27.66

-25.85

20.07

Agriculture Agrarian Reform Natural Resources Industry Trade Tourism Power & Energy Water Resources Devt.

Transp. & Comm.

Other Econ. Services

9.84 3.72 10.83 18.90 2.76 8.54 -3.02 35.48 9.02 38.95

13.51 29.22 19.11 3.98 -5.16 21.10 22.67 5.18 16.98 -36.60

20.24 18.89 23.20 11.89 14.14 23.24 1.08 4.37 11.95 59.24

23.07 12.42 14.41 9.61 33.66 47.45 -78.19 25.87 3.59 -16.20

52.64 44.92 65.98 2.04 3.83 28.48 120.59 18.57 19.48 -15.59

-38.73 63.75 -37.49 -31.54 -17.07 -37.21 -50.62 -86.12 -17.39 -89.07

31.13 27.39 2.99 21.98 35.83 9.75 -55.66 48.17 20.69 -69.19

15.60

19.52

19.29

25.49

21.73

11.28

7.52

16.02 14.45 7.63 25.75

21.29 20.64 22.34 -18.50

20.21 6.48 30.24 47.61

20.45 34.56 42.95 55.23

27.28 26.17 10.97 -47.24

11.39 -6.03 31.33 -10.81

6.32 2.11 11.49 62.89

5.81

15.25

17.33

13.02

20.22

2.91

-2.39

17.28

22.66

15.50

22.63

14.62

7.37

3.78

13.89 30.73

23.89 20.01

15.37 15.83

21.52 25.34

14.99 13.74

7.22 7.73

-1.98 17.45

Others

17.90

22.33

28.69

6.43

22.32

46.73

8.81

Debt Service

34.68

28.63

2.84

-14.29

6.72

33.65

12.63

13.77

15.25

18.46

13.50

21.85

6.20

8.60

Total Social Services Education Health Social Welfare and Employment Housing & Com. Devt.

National Defense Total Public Services Public Administration Peace and Order

MEMO ITEM: Grand Total Less Debt Service

Source: Mini Budget, Department of Budget and Management

Table IV.5 NATIONAL GOVERNMENT EXPENDITURES AS A PROPORTION OF GNP, BY SECTORAL CLASSIFICATION, 1975-1999 (%)

75-85 GRAND TOTAL

AVERAGE 86-92 93-97

1996

1997

1998P

1999gaa

15.67

21.57

21.17

20.23

21.35

21.78

21.28

Total Economic Services

6.20

4.51

4.08

3.77

4.31

2.90

3.10

Agriculture Agrarian Reform Natural Resources Industry Trade Tourism Power & Energy Water Resources Devt.

Transp. & Comm.

Other Econ. Services

0.79 0.08 0.25 0.31 0.04 0.03 0.77 0.14 2.71 1.08

0.75 0.27 0.29 0.16 0.01 0.02 0.31 0.08 2.14 0.48

0.69 0.15 0.28 0.12 0.01 0.03 0.21 0.05 2.29 0.27

0.67 0.14 0.25 0.12 0.01 0.03 0.05 0.04 2.19 0.27

0.92 0.18 0.37 0.11 0.01 0.04 0.10 0.05 2.34 0.21

0.51 0.26 0.21 0.07 0.01 0.02 0.04 0.01 1.75 0.02

0.60 0.29 0.19 0.07 0.01 0.02 0.02 0.01 1.88 0.01

3.16

3.94

4.13

4.46

4.85

4.89

4.69

1.87 0.57 0.24 0.47

2.74 0.67 0.23 0.30

3.12 0.45 0.44 0.13

3.25 0.46 0.54 0.21

3.71 0.52 0.53 0.10

3.74 0.44 0.64 0.08

3.54 0.40 0.63 0.11

National Defense

1.78

1.31

1.38

1.37

1.48

1.38

1.20

Total Public Services

1.70

2.53

2.73

2.82

2.90

2.82

2.60

1.16 0.54

1.94 0.59

1.94 0.79

1.98 0.84

2.04 0.86

1.98 0.83

1.73 0.87

Others

0.82

0.90

2.70

2.59

2.84

3.77

3.65

Debt Service

2.01

8.38

6.14

5.21

4.97

6.02

6.04

13.66

13.19

15.03

15.02

16.38

15.75

15.24

Total Social Services Education Health Social Welfare and Employment Housing and Community Developmnet

Public Administration Peace and Order

MEMO ITEM: Grand Total Less Debt Service

Source: Mini Budget, Department of Budget and Management

ROPORTION OF GNP, BY SECTORAL CLASSIFICATION, 1975-1999

TABLE IV.6 EVOLUTION OF 1998 NATIONAL GOVERNMENT BUDGET (In Million Pesos )

Nominal

RATIO

RATIO

1997

1998

1998

1998

98 Prelim/

98 Prelim/

Actual

President's

GAA

Preliminary

1998 GAA

98 PRESIDENT'S

Actual

539,461

590,702

641,674

607,377

0.9466

1.0282

73,165

83,509

86,692

78,559

0.9062

0.9407

51,554 21,611

59,423 24,086

62,368 24,324

55,278 23,282

0.8863 0.9572

0.9302 0.9666

37,366

45,487

46,492

38,454

0.8271

0.8454

122,668

144,954

152,301

137,106

0.9002

0.9459

93,639 13,062 13,493 2,474

107,144 13,770 20,113 3,126

109,130 14,506 23,418 4,447

104,301 12,274 17,720 2,207

0.9558 0.8462 0.7567 0.4962

0.9735 0.8914 0.8810 0.7059

Total Economic Services

108,952

101,918

115,159

80,786

0.7015

0.7927

Agrarian Reform Agriculture Natural Resource Industry Trade Tourism Power Water Transportation Other Economic Services

4,426 23,225 9,336 2,766 215 940 2,541 1,175 59,101 5,227

8,371 17,221 6,687 2,031 213 677 3,968 362 62,057 330

8,426 18,372 6,626 2,288 213 810 1,495 422 76,164 343

7,247 14,229 5,836 1,894 178 590 1,255 163 48,823 572

0.8601 0.7745 0.8808 0.8276 0.8364 0.7284 0.8392 0.3864 0.6410 1.6678

0.8657 0.8263 0.8727 0.9325 0.8364 0.8715 0.3161 0.4505 0.7867 1.7310

125,649

125,459

125,459

167,927

1.3385

1.3385

71,661

90,175

116,371

105,147

0.9036

1.1660

413,812

465,243

516,215

439,450

0.8513

0.9446

16.38

16.68

18.51

15.75

GRAND TOTAL Total Public Administration

Public Administration Peace & Order National Defense Total Social Services

Education Health Social Welfare & Employment Housing & Community Development

Debt Service Others MEMO ITEM: Grand Total Less Debt Service Percent of GNP Source: Department of Budget and Management

Table IV.7 PER CAPITA NATIONAL GOVERNMENT EXPENDITURE in 1985 Prices, 1996-1999

75-85

Average 86-92

93-97

1996

1997

1998

1999F

1901.00

2408.04

2561.33

2517.49

2733.04

2736.47

2700.25

Total Economic Services

775.87

512.23

492.07

469.76

551.98

363.97

371.36

Agriculture Agrarian Reform Natural Resources Industry Trade Tourism Power & Energy Water Resources Devt.

Transp. & Comm.

Other Econ. Services

104.09 12.26 33.57 34.98 6.84 4.39 107.14 18.02 359.84 94.75

90.28 29.75 31.80 19.73 0.92 2.49 34.35 9.43 228.06 65.43

81.24 17.51 32.55 14.06 1.12 3.57 27.35 6.27 275.35 33.05

83.75 16.81 30.96 14.92 1.14 4.03 6.34 5.46 272.27 34.09

117.66 22.42 47.30 14.01 1.09 4.76 12.87 5.95 299.42 26.48

64.11 32.65 26.29 8.53 0.80 2.66 5.65 0.73 219.97 2.58

69.63 37.51 24.58 9.45 1.02 2.69 2.81 0.98 219.42 3.27

388.49

444.16

490.16

554.70

621.47

617.72

605.38

229.59 70.45 32.26 56.19

305.50 74.32 23.92 40.41

370.01 53.84 51.31 15.01

404.97 56.98 66.93 25.82

474.40 66.17 68.36 12.54

469.92 55.30 79.84 12.66

447.81 50.92 89.77 16.88

National Defense

249.83

148.66

166.21

171.09

189.31

173.25

152.62

Total Public Services

206.34

281.05

327.95

351.36

370.67

353.94

332.44

144.14 62.20

214.83 66.22

233.01 94.93

246.77 104.59

261.18 109.49

249.05 104.89

222.10 110.34

96.73

94.98

325.25

322.48

363.05

471.01

470.18

183.75

926.96

759.69

648.10

636.57

756.58

768.28

72.19 1717.25

84.03 1481.08

317.58 1801.64

311.52 1869.39

359.95 2096.47

328.41 1979.89

393.12 1931.98

GRAND TOTAL

Total Social Services Education Health Social Welfare and Employment Housing and Community Development

Public Administration Peace and Order Others Debt Service MEMO ITEM: IRA Grand Total Less Debt Service Source: Department of Budget and Management.

Table IV.8 DEPARTMENT OF HEALTH, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only) As of September 30, 1998 (Current)

Ratio of Allotments to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Allotments PS MOE CO TOTAL

A. PROGRAMS AND ACTIVITIES I. General Administration and Support

0.3700

0.7500

II. Support to Operations

1.0000

0.7036

1.0000 1.0000 1.0000 1.0000

0.7011 0.7327 0.8815 0.6980

1.0000 1.0000

III. Operations a. Public Health Services 1. Family Health Nutrition and Welfare a. Maternal and Child Health Service b. Nutrition Service including Salt Iodization Program c. Family Planning Service d. Dental Health Service e. Control of Diarrheal Diseases f. Immunization Program g. Control of Acute Respiratory Infection/ Integrated Child Care Management h. Family Health Program 2. National Disease Control Program a. Communicable Disease Control Program 1. Communicable Disease Control Service 2. Tuberculosis Control a. Tuberculosis Control Services b. Philippine Tuberculosis Society c. National Tuberculosis Control Program 3. STD/AIDS Control Program 4. Malaria Control Program 5. Rabies Control Program 6. Schistosomiasis Control Service 7. Dengue Control Program 8. Filaria Control Program 9. National Leprosy Elimination Program b. Non-communicable Disease Control Program 1. Non-communicable Disease Control Service 2. Cardiovascular Disease Control 3. Smoking Cessation Program 4. Cancer Control Program 5. Blindess Prevention Program 6. Preventive Nephrology 7. National Preventive Mental Health Program 8. Occupational Health Program 9. National Diabetes Program

1.0000 1.0000 1.0000 1.0000 1.0000

1.0000 1.0000 1.0000

1.0000 1.0000

0.4190

0.1623

0.3733

0.7500

0.7770

0.4678

0.3269

1.0000 1.0000 1.0000

0.7285 0.7485 0.9109 0.7248

0.6469 0.6576 0.6087 0.6952

0.2209 0.2003 0.1903 0.4281

0.7500 0.7500 1.0000 0.6866 1.0000

0.7836 0.8462 1.0000 0.6866 1.0000

0.7058 0.6338

0.5013 0.6862 0.7268 0.7502 0.7500 0.7500 0.7500 0.7500 0.5614 0.7500 0.7500 0.7500 0.7500 0.7495 0.7500 0.6053 0.7378 0.5656 0.7500 0.4766 0.7500 0.5923 0.9304 0.7500 0.5000

0.5013 0.7130 0.7548 0.9575 0.7584 0.8763 0.7500 0.7500 0.5989 0.8111 0.7500 0.9085 0.7500 0.7495 0.7500 0.6250 0.8670 0.5656 0.7500 0.4766 0.7500 0.5923 0.9304 0.7500 0.5000

0.6454 0.6484 0.6598 0.6198 0.6198

0.4935 0.6466 0.7047

0.6325 0.6325

0.1895

0.4388

0.4977

0.0000

0.3569

0.4678

0.4646

0.0000

0.4593

0.0391 0.0391 0.0391

0.2569 0.2211 0.2370 0.4518

0.6469 0.6576 0.6087 0.6952

0.3151 0.2734 0.2159 0.6134

0.0391 0.0391 0.0391

0.3527 0.2954 0.2602 0.6234

0.2292 0.1419 0.0021 0.1259 0.5627

0.2933 0.3312 0.0021 0.1259 0.5627

0.7058 0.6338

0.3056 0.1892 0.0021 0.1833 0.5627

0.3743 0.3913 0.0021 0.1833 0.5627

0.0933 0.2279 0.1770 0.4709 0.1043 0.4029 0.6250 0.0165 0.3002 0.4828 0.0301 0.2241 0.7037 0.1513 0.2912 0.3290 0.2198 0.4546 0.3158 0.1237 0.4577 0.2947 0.7780 0.6099 0.0747

0.0933 0.2636 0.2253 0.6277 0.1217 0.5125 0.6250 0.0165 0.3167 0.5229 0.0301 0.5288 0.7037 0.1513 0.2912 0.3441 0.4232 0.4546 0.3158 0.1237 0.4577 0.2947 0.7780 0.6099 0.0747

0.1861 0.3321 0.2435 0.6277 0.1391 0.5372 0.8333 0.0220 0.5347 0.6438 0.0401 0.2988 0.9383 0.2019 0.3882 0.5436 0.2979 0.8038 0.4210 0.2595 0.6103 0.4975 0.8362 0.8132 0.1494

0.1861 0.3697 0.2984 0.6555 0.1604 0.5849 0.8333 0.0220 0.5288 0.6447 0.0401 0.5821 0.9383 0.2019 0.3882 0.5506 0.4881 0.8038 0.4210 0.2595 0.6103 0.4975 0.8362 0.8132 0.1494

0.6454 0.6484 0.6598 0.6198 0.6198

0.4935 0.6466 0.7047

0.6325 0.6325

0.4524

Table IV.8 DEPARTMENT OF HEALTH, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only) As of September 30, 1998 (Current)

Ratio of Allotments to Appropriations PS MOE CO TOTAL 3. Environmental Health Program a. Environmental Health Service b. Operation of Inter-Agency Committee on Environmental Health c. Hospital Waste Management 4. Community Health Program a. Community Health Service b. Traditional Medicine Program c. Health Development Program d. Community-based Rehabilitation Program e. Indigenous People 5. Provision for a pool of eighty (80) Rural Health Physicians for Doctorless Communities b. Primary Health Care Program c. Health Facilities Maintenance and Operations d. Health Facility Standards, Regulations and Licensing e. Drugs and Medicines j. Women and Children Protection Program k. Regional Assistance Fund for Drugs & Micronutrients

1.0000 1.0000 1.0000

0.7500 0.7500 0.7497

0.8181 0.8302 0.7825

0.7500 0.5244 0.7500 0.6175 0.4007 0.7500 0.7500 0.5470

0.7500 0.5618 0.8811 0.6175 0.4007 0.7500 0.7500 0.8441

0.0000 0.9912 1.0000 0.9388

0.7488 0.7891 0.7500 0.2174 0.0491 0.7500

0.7014 0.8532 0.8554 0.2365 0.0491 0.7500

Subtotal, III

0.9877

0.6885

0.9716

TOTAL A

0.5864

0.6919

0.9617

1.0000 1.0000

1.0000

0.9900 0.7500

Ratio of Obligations to Appropriations PS MOE CO TOTAL 0.7852 0.7882 0.6893

Ratio of Obligations to Allotments PS MOE CO TOTAL

0.4621 0.5419 0.4410

0.5502 0.6209 0.4735

0.0802 0.2831 0.1757 0.1040 0.3398 0.7330 0.0000 0.2403

0.0802 0.3086 0.4019 0.1040 0.3398 0.7330 0.0000 0.4747

0.0000 0.6224 0.6633 0.4672

0.2496 0.6134 0.4508 0.0199 0.0000 0.7500

0.2338 0.5209 0.4793 0.0317 0.0000 0.7500

0.7271

0.6343

0.2839

0.0662

0.3101

0.6422

0.4123

0.0682

0.4266

0.6717

0.3138

0.2907

0.0633

0.2907

0.5351

0.4201

0.0658

0.4328

1.0000

1.0000

0.0000

1.0000 0.0276

0.6069 0.6069

0.5978

0.0762 0.0000

0.7852 0.7882 0.6893

0.6069 0.6069

0.5978

0.6279 0.6633 0.4976

0.6162 0.7225 0.5882

0.6725 0.7479 0.6051

0.1069 0.5398 0.2343 0.1684 0.8480 0.9773 0.0000 0.4392

0.1069 0.5492 0.4561 0.1684 0.8480 0.9773 0.0000 0.5624

0.3333 0.7773 0.6011 0.0915 0.0000 1.0000

0.0769 0.0000

0.3333 0.6105 0.5604 0.1342 0.0000 1.0000

B. PROJECTS I. Locally-Funded Project(s) a. Construction, Improvement, Repair and Rehabilitation/ Renovation including the Purchase of Equipment of Special Hospitals, Medical Centers, Sanitaria, Regional Hospitals, Central Office, Regional Field Office and Other Related Facilities on a Priority Basis as may be Determined by the Secretary of Health b. Health Status Survey f. Construction and Expansion of the Baguio General Hospital, Baguio City h. Assistance to Mandaluyong Medical Center, Mandaluyong City i. Procurement of Medicines and Health Kits j. Construction of Deep Wells for National Mental Health

0.7500

0.0000

0.0041

0.0267

0.0230 3.7500

0.0230

3.1676 0.1883

0.0312

0.0745

0.6673

0.2295

0.6015

0.0267 0.0230

TOTAL B GRAND TOTAL Source: Department of Health, Office of the Secretary

0.7500 0.0653

0.7500

0.0168

0.5864

0.3138

0.0000

0.7500 0.0018

1.0000 0.0371

0.0000

0.0041

1.0000

3.1676

0.0230 3.7500

1.0000 1.0000

0.1068

0.0200

0.0439

0.2817

0.0292

0.2617

0.5351

1.0000

1.0000

1.0000 1.0000

0.5670

0.6412

0.5895

0.4222

0.1273

0.4351

Table IV.9 DEPARTMENT OF HEALTH, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only) As of December 30, 1998 (Current)

Ratio of Allotments to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Allotments PS MOE CO TOTAL

A. PROGRAMS AND ACTIVITIES I. General Administration and Support

0.3700

0.7500

II. Support to Operations

1.0000

0.7036

1.0000 1.0000 1.0000 1.0000

0.9075 0.9698 0.9427 0.9637

1.0000 1.0000

III. Operations a. Public Health Services 1. Family Health Nutrition and Welfare a. Maternal and Child Health Service b. Nutrition Service including Salt Iodization Program c. Family Planning Service d. Dental Health Service e. Control of Diarrheal Diseases f. Immunization Program g. Control of Acute Respiratory Infection/ Integrated Child Care Management h. Family Health Program 2. National Disease Control Program a. Communicable Disease Control Program 1. Communicable Disease Control Service 2. Tuberculosis Control a. Tuberculosis Control Services b. Philippine Tuberculosis Society c. National Tuberculosis Control Program 3. STD/AIDS Control Program 4. Malaria Control Program 5. Rabies Control Program 6. Schistosomiasis Control Service 7. Dengue Control Program 8. Filaria Control Program 9. National Leprosy Elimination Program b. Non-communicable Disease Control Program 1. Non-communicable Disease Control Service 2. Cardiovascular Disease Control 3. Smoking Cessation Program 4. Cancer Control Program 5. Blindess Prevention Program 6. Preventive Nephrology 7. National Preventive Mental Health Program 8. Occupational Health Program 9. National Diabetes Program 3. Environmental Health Program a. Environmental Health Service b. Operation of Inter-Agency Committee on Environmental Health c. Hospital Waste Management

1.0000 1.0000 1.0000 1.0000 1.0000

1.0000 1.0000 1.0000

1.0000 1.0000

1.0000 1.0000 1.0000

0.4190

0.2537

0.5786

0.7500

0.7770

0.9883

0.5432

1.0000 1.0000 1.0000

0.9159 0.9716 0.9569 0.9669

0.9980 0.9999 1.0000 0.9998

0.4402 0.3568 0.2869 0.5499

0.8802 0.9113 1.0000 1.0000 1.0000

0.8963 0.9454 1.0000 1.0000 1.0000

1.0000 1.0000

0.6833 0.8632 0.9139 0.9063 0.9609 0.8939 0.7500 0.9943 0.6305 0.8654 0.9790 0.8568 0.9732 0.8245 0.9388 0.7624 0.8674 0.7032 0.9572 0.5227 0.7964 0.8794 1.0000 0.9218 0.9357 0.8467 0.8322 0.8977

0.6833 0.8749 0.9228 0.9841 0.9622 0.9475 0.7500 0.9943 0.6621 0.8983 0.9790 0.9476 0.9732 0.8245 0.9388 0.7742 0.9327 0.7032 0.9572 0.5227 0.7964 0.8794 1.0000 0.9218 0.9357 0.8885 0.8860 0.9112

0.8938

0.8938

0.9953 0.9943 0.9878 0.9872 0.9872

1.0000 0.9952 1.0000

0.9995 0.9995

0.9984 1.0000 0.9471

0.2956

0.6857

0.7715

0.7500

0.6554

0.9883

0.7720

1.0000

0.8435

0.0391 0.0391 0.0391

0.4865 0.3851 0.3675 0.5898

0.9980 0.9999 1.0000 0.9998

0.4851 0.3679 0.3043 0.5706

0.0391 0.0391 0.0391

0.5312 0.3963 0.3841 0.6100

0.4945 0.2195 0.0070 0.3109 0.5627

0.5625 0.5198 0.0070 0.3109 0.5627

1.0000 1.0000

0.5618 0.2408 0.0070 0.3109 0.5627

0.6276 0.5498 0.0070 0.3109 0.5627

0.2614 0.5424 0.5826 0.7248 0.6021 0.5646 0.7500 0.5821 0.3629 0.5213 0.7053 0.3375 0.7182 0.6399 0.7171 0.4627 0.4455 0.5130 0.7121 0.2273 0.5871 0.5095 0.8251 0.6624 0.1700 0.5514 0.6397 0.5738

0.2614 0.5812 0.6248 0.9431 0.6151 0.7782 0.7500 0.5821 0.4174 0.6371 0.7053 0.7576 0.7182 0.6399 0.7171 0.4894 0.7185 0.5130 0.7121 0.2273 0.5871 0.5095 0.8251 0.6624 0.1700 0.6732 0.7553 0.6227

0.3825 0.6284 0.6374 0.7997 0.6267 0.6316 1.0000 0.5855 0.5756 0.6023 0.7204 0.3938 0.7380 0.7761 0.7639 0.6069 0.5136 0.7295 0.7439 0.4348 0.7372 0.5794 0.8251 0.7185 0.1816 0.6513 0.7687 0.6391

0.3825 0.6642 0.6771 0.9584 0.6392 0.8213 1.0000 0.5855 0.6304 0.7092 0.7204 0.7994 0.7380 0.7761 0.7639 0.6321 0.7704 0.7295 0.7439 0.4348 0.7372 0.5794 0.8251 0.7185 0.1816 0.7578 0.8525 0.6835

0.1068

0.1068

0.1195

0.1195

0.9953 0.9943 0.9878 0.9872 0.9872

1.0000 0.9952 1.0000

0.9995 0.9995

0.9984 1.0000 0.9471

0.7055

Table IV.9 DEPARTMENT OF HEALTH, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only) As of December 30, 1998 (Current)

Ratio of Allotments to Appropriations PS MOE CO TOTAL 4. Community Health Program a. Community Health Service b. Traditional Medicine Program c. Health Development Program d. Community-based Rehabilitation Program e. Indigenous People 5. Provision for a pool of eighty (80) Rural Health Physicians for Doctorless Communities b. Primary Health Care Program c. Health Facilities Maintenance and Operations d. Health Facility Standards, Regulations and Licensing e. Drugs and Medicines j. Women and Children Protection Program k. Regional Assistance Fund for Drugs & Micronutrients

1.0000 1.0000

0.7104 0.9129 0.7382 0.6145 0.9470 1.0000 0.7154

0.7332 0.9586 0.7382 0.6145 0.9470 1.0000 0.9020

0.0000 0.9912 1.0000 0.9388

0.7488 0.8500 0.7500 0.8655 0.0491 0.7500

0.7014 0.8947 0.8554 0.8675 0.0491 0.7500

Subtotal, III

0.9877

0.8812

0.9716

TOTAL A

0.5864

0.8613

0.9617

1.0000

0.9900 0.7500

Ratio of Obligations to Appropriations PS MOE CO TOTAL 1.0000 1.0000

Ratio of Obligations to Allotments PS MOE CO TOTAL

0.4286 0.3377 0.5052 0.3448 0.7329 0.6755 0.2407

0.4736 0.6851 0.5052 0.3448 0.7329 0.6755 0.7386

0.0000 0.9911 0.9961 0.9083

0.4040 0.7498 0.5504 0.4140 0.0050 0.7500

0.3784 0.6670 0.6659 0.4271 0.0050 0.7500

0.8946

0.9857

0.4879

0.0675

0.5214

0.9979

0.5537

0.0694

0.5828

0.7929

0.5092

0.4958

0.0979

0.4889

0.8684

0.5756

0.1018

0.6166

0.4895

0.4895

0.9045

1.0000 0.3210

1.0000

0.0762 0.0153

1.0000 1.0000

1.0000

0.9999 0.9961 0.9675

0.6033 0.3699 0.6844 0.5611 0.7739 0.6755 0.3365 0.5395 0.8822 0.7339 0.4783 0.1024 1.0000

0.6459 0.7147 0.6844 0.5611 0.7739 0.6755 0.8188

0.0769 0.0204

0.5395 0.7455 0.7784 0.4924 0.1024 1.0000

B. PROJECTS I. Locally-Funded Project(s) a. Construction, Improvement, Repair and Rehabilitation/ Renovation including the Purchase of Equipment of Special Hospitals, Medical Centers, Sanitaria, Regional Hospitals, Central Office, Regional Field Office and Other Related Facilities on a Priority Basis as may be Determined by the Secretary of Health b. Health Status Survey f. Construction and Expansion of the Baguio General Hospital, Baguio City h. Assistance to Mandaluyong Medical Center, Mandaluyong City i. Procurement of Medicines and Health Kits j. Construction of Deep Wells for National Mental Health

0.7500

Sub-allotment Automatic Appropriation (Life & Retirement) Productivity Incentive Bonus Miscellaneous Personnel Benefits TOTAL SUB-ALLOTMENT GRAND TOTAL

Source: Department of Health

0.0000

0.0041

0.0000

0.0230 3.7500

0.0000

3.1676 0.1883

0.0454

0.0848

0.8285

0.2406

0.7097

0.0267 0.0230

TOTAL B TOTAL

0.7500 0.0653

0.7500

0.0168

0.5864

0.8576

0.8305

0.2406

0.7729

0.5092

0.7765

0.0152

0.7500 0.0210

1.0000 0.1186

0.0000

0.0000

0.0000

3.1676

0.0000 3.1676

0.0000 0.0000

1.0000

0.0000 0.8447

0.0894

0.0301

0.0465

0.4749

0.6637

0.5480

0.4760

0.0446

0.4369

0.8684

0.5745

0.1852

0.6156

0.4991

0.9832 1.0000 0.6376 0.9857 0.9055

0.1852

0.9832 1.0000 0.8867 0.9853 0.6458

0.4779

0.0446

0.9662 0.9662 0.5754

0.0000

Table IV.9 DEPARTMENT OF HEALTH, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only)

Ratio of Allotments to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Allotments PS MOE CO TOTAL

A. PROGRAMS AND ACTIVITIES I. General Administration and Support

0.3700

0.7500

0.4190

0.3683

0.5786

0.3954

0.9955

0.7715

0.9437

II. Support to Operations

1.0000

0.7036

0.7500

0.7770

0.9883

0.5432

0.7500

0.6554

0.9883

0.7720

1.0000 0.8435

1.0000 1.0000 1.0000 1.0000

0.9075 0.9698 0.9427 0.9637

1.0000 1.0000 1.0000

0.9159 0.9716 0.9569 0.9669

0.9980 0.9999 1.0000 0.9998

0.4402 0.3568 0.2869 0.5499

0.0391 0.0391 0.0391

0.4865 0.3851 0.3675 0.5898

0.9980 0.9999 1.0000 0.9998

0.4851 0.3679 0.3043 0.5706

0.0391 0.5312 0.0391 0.3963 0.0391 0.3841 0.6100

1.0000 1.0000

0.8802 0.9113 1.0000 1.0000 1.0000

0.8963 0.9454 1.0000 1.0000 1.0000

1.0000 1.0000

0.4945 0.2195 0.0070 0.3109 0.5627

0.5625 0.5198 0.0070 0.3109 0.5627

1.0000 1.0000

0.5618 0.2408 0.0070 0.3109 0.5627

0.6276 0.5498 0.0070 0.3109 0.5627

0.6833 0.8632 0.9139 0.9063 0.9609 0.8939 0.7500 0.9943 0.6305 0.8654 0.9790 0.8568 0.9732 0.8245 0.9388 0.7624 0.8674 0.7032 0.9572 0.5227 0.7964 0.8794 1.0000 0.9218 0.9357 0.8467 0.8322 0.8977

0.6833 0.8749 0.9228 0.9841 0.9622 0.9475 0.7500 0.9943 0.6621 0.8983 0.9790 0.9476 0.9732 0.8245 0.9388 0.7742 0.9327 0.7032 0.9572 0.5227 0.7964 0.8794 1.0000 0.9218 0.9357 0.8885 0.8860 0.9112

0.2614 0.5424 0.5826 0.7248 0.6021 0.5646 0.7500 0.5821 0.3629 0.5213 0.7053 0.3375 0.7182 0.6399 0.7171 0.4627 0.4455 0.5130 0.7121 0.2273 0.5871 0.5095 0.8251 0.6624 0.1700 0.5514 0.6397 0.5738

0.2614 0.5812 0.6248 0.9431 0.6151 0.7782 0.7500 0.5821 0.4174 0.6371 0.7053 0.7576 0.7182 0.6399 0.7171 0.4894 0.7185 0.5130 0.7121 0.2273 0.5871 0.5095 0.8251 0.6624 0.1700 0.6732 0.7553 0.6227

0.3825 0.6284 0.6374 0.7997 0.6267 0.6316 1.0000 0.5855 0.5756 0.6023 0.7204 0.3938 0.7380 0.7761 0.7639 0.6069 0.5136 0.7295 0.7439 0.4348 0.7372 0.5794 0.8251 0.7185 0.1816 0.6513 0.7687 0.6391

0.3825 0.6642 0.6771 0.9584 0.6392 0.8213 1.0000 0.5855 0.6304 0.7092 0.7204 0.7994 0.7380 0.7761 0.7639 0.6321 0.7704 0.7295 0.7439 0.4348 0.7372 0.5794 0.8251 0.7185 0.1816 0.7578 0.8525 0.6835

0.8938

0.8938

0.1068

0.1068

0.1195

0.1195

III. Operations a. Public Health Services 1. Family Health Nutrition and Welfare a. Maternal and Child Health Service b. Nutrition Service including Salt Iodization Program c. Family Planning Service d. Dental Health Service e. Control of Diarrheal Diseases f. Immunization Program g. Control of Acute Respiratory Infection/ Integrated Child Care Management h. Family Health Program 2. National Disease Control Program a. Communicable Disease Control Program 1. Communicable Disease Control Service 2. Tuberculosis Control a. Tuberculosis Control Services b. Philippine Tuberculosis Society c. National Tuberculosis Control Program 3. STD/AIDS Control Program 4. Malaria Control Program 5. Rabies Control Program 6. Schistosomiasis Control Service 7. Dengue Control Program 8. Filaria Control Program 9. National Leprosy Elimination Program b. Non-communicable Disease Control Program 1. Non-communicable Disease Control Service 2. Cardiovascular Disease Control 3. Smoking Cessation Program 4. Cancer Control Program 5. Blindess Prevention Program 6. Preventive Nephrology 7. National Preventive Mental Health Program 8. Occupational Health Program 9. National Diabetes Program 3. Environmental Health Program a. Environmental Health Service b. Operation of Inter-Agency Committee on Environmental Health c. Hospital Waste Management

1.0000 1.0000 1.0000 1.0000 1.0000

1.0000 1.0000 1.0000

1.0000 1.0000

1.0000 1.0000 1.0000

0.9953 0.9943 0.9878 0.9872 0.9872

1.0000 0.9952 1.0000

0.9995 0.9995

0.9984 1.0000 0.9471

0.9953 0.9943 0.9878 0.9872 0.9872

1.0000 0.9952 1.0000

0.9995 0.9995

0.9984 1.0000 0.9471

Table IV.9 DEPARTMENT OF HEALTH, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only)

Ratio of Allotments to Appropriations PS MOE CO TOTAL 4. Community Health Program a. Community Health Service b. Traditional Medicine Program c. Health Development Program d. Community-based Rehabilitation Program e. Indigenous People 5. Provision for a pool of eighty (80) Rural Health Physicians for Doctorless Communities b. Primary Health Care Program c. Health Facilities Maintenance and Operations d. Health Facility Standards, Regulations and Licensing e. Drugs and Medicines j. Women and Children Protection Program k. Regional Assistance Fund for Drugs & Micronutrients

1.0000 1.0000

Ratio of Obligations to Appropriations PS MOE CO TOTAL

0.7104 0.9129 0.7382 0.6145 0.9470 1.0000 0.7154

0.7332 0.9586 0.7382 0.6145 0.9470 1.0000 0.9020

1.0000 1.0000

0.0000 0.9912 1.0000 0.9388

0.7488 0.8500 0.7500 0.8655 0.0491 0.7500

0.7014 0.8947 0.8554 0.8675 0.0491 0.7500

Subtotal, III

0.9877

0.8812

0.9716

TOTAL A

0.5864

0.8613

0.9617

1.0000

0.9900 0.7500

0.4286 0.3377 0.5052 0.3448 0.7329 0.6755 0.2407

0.4736 0.6851 0.5052 0.3448 0.7329 0.6755 0.7386

0.0000 0.9911 0.9961 0.9083

0.4040 0.7498 0.5504 0.4140 0.0050 0.7500

0.3784 0.6670 0.6659 0.4271 0.0050 0.7500

0.8946

0.9857

0.4879

0.0675

0.5214

0.7929

0.5838

0.4958

0.0979

0.5082

1.0000

0.0762 0.0153

Ratio of Obligations to Allotments PS MOE CO TOTAL 1.0000 1.0000

0.6033 0.3699 0.6844 0.5611 0.7739 0.6755 0.3365

0.6459 0.7147 0.6844 0.5611 0.7739 0.6755 0.8188

0.5395 0.8822 0.7339 0.4783 0.1024 1.0000

0.5395 0.0769 0.7455 0.0204 0.7784 0.4924 0.1024 1.0000

0.9979

0.5537

0.0694 0.5828

0.9956

0.5756

0.1018 0.6409

1.0000

0.9999 0.9961 0.9675

B. PROJECTS I. Locally-Funded Project(s) a. Construction, Improvement, Repair and Rehabilitation/ Renovation including the Purchase of Equipment of Special Hospitals, Medical Centers, Sanitaria, Regional Hospitals, Central Office, Regional Field Office and Other Related Facilities on a Priority Basis as may be Determined by the Secretary of Health b. Health Status Survey f. Construction and Expansion of the Baguio General Hospital, Baguio City h. Assistance to Mandaluyong Medical Center, Mandaluyong City i. Procurement of Medicines and Health Kits j. Construction of Deep Wells for National Mental Health TOTAL B TOTAL Sub-allotment Automatic Appropriation (Life & Retirement) Miscellaneous Personnel Benefits TOTAL SUB-ALLOTMENT GRAND TOTAL Source: Department of Health , Office of the Secretary

0.5864

0.7794

0.4895 0.4895

0.7500

0.0267

0.7500 0.0653

0.7500

0.0168 0.0000

0.0041

0.0000 0.0000

3.1676

0.0230 3.7500

0.0230

0.1883

0.0454

0.0848

0.8285

0.2406

0.7097

0.8305

0.2406

0.7550

0.5838

0.7729

0.0152

0.7500 0.0210

1.0000 0.1186

1.0000 0.9045 0.3210

0.0000

0.0000

0.0000

0.0000

3.1676

0.0000 3.1676

0.0000 0.0000

0.0000 1.0000 0.8447

0.0894

0.0301

0.0465

0.4749

0.6637 0.5480

0.4760

0.0446

0.4539

0.9956

0.5745

0.1852 0.6396

0.4983

0.9832 0.6376 0.9799 0.9917

0.9662 0.9662 0.5754

0.9832 0.8867 0.9795 0.1852 0.6600

0.4779

0.0446

Table IV.10 DEPARTMENT OF EDUCATION, CULTURE AND SPORTS, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only) For the Period Ending December 31, 1998

Ratio of Allotments to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Appropriations PS MOE CO TOTAL

Ratio of Obligations to Allotments PS MOE CO TOTAL

A. PROGRAMS AND ACTIVITIES I. General Administration and Support a. General Administration and Support Services a. General Management and Supervision 1. General administrative services 1.00000 b. Operation and Maintenance of Centers 1.00000 c. Human Resources Training and Development including an amount of P15 Million for Teacher's Training d. Contributions to Various Activities e. Out-of-School Adult Education Program Subtotal, I II. Support to Operations

0.75479 0.90165 0.61543

0.50000 1.00000

0.80884 0.75000

1.00000

0.76858

1.00000

0.88745 0.91704 0.63447

1.00000 1.00000

0.80884 0.75000 0.66667

0.75479 0.90165 0.61543

0.50000 1.00000

0.80884 0.75000

0.86309

1.00000

0.76858

0.68302

0.88246

1.00000

0.00000

0.24074 0.81518

0.24128 0.81518

0.75000

0.75000 1.00000 1.00000

0.75000

1.00000 1.00000 0.75000

0.00000

0.47949

0.55782

0.88745 0.91704 0.63447

1.00000 1.00000

0.80884 0.75000 0.66667

1.00000 1.00000 1.00000

1.00000 1.00000

1.00000 1.00000

0.86309

1.00000

1.00000

0.68302

0.88246

1.00000

1.00000

0.00000

0.24074 0.81518

1.00000 1.00000

0.75000

0.75000 1.00000 1.00000

0.00000

1.00000 1.00000 0.00000

0.00000

0.47949

1.00000

1.00000 1.00000 1.00000 1.00000 1.00000

1.00000

1.00000 1.00000

III. Operations e. Regional Operations 16. NATIONWIDE a. Requirements of Newly-Created Positions 3. Requirements for the following Positions Authorized in 1996 Subject to Actual Deployment by Municipalities a. Teacher I Positions (2,000 Items) 0.24128 b. Public Health Nurse Positions (2,240 Items) 0.81518 b. Government Assistance to Students and Teachers in private Education (GASTPE) c. Lump-sum for Reclassification of Positions d. Lump-sum for Subsistence and Laundry Allowance e. Pre-School Education f. Secondary Education 1. Operational Expenses of Newly-Legislated/ Established High Schools h. Purchase of Desks, Chairs, Textbooks, Instructional Materials, Tools, Furniture, Fixtures, Computers and other Equipment m. Lump-sum for Land and Land Improvement Outlay Subtotal, III Total Source: DECS, Office of the Secretary

1.00000 1.00000

0.55782

0.51265

0.00000

0.37714

0.19595

0.19595

0.00000

0.00000

0.00000

0.17380

0.17380

1.00000 1.00000 1.00000

1.00000

0.00000

1.00000 1.00000 0.00000 1.00000

0.00000

0.00000

0.88697

0.88697

0.58351

0.66390

0.03403

0.58369

0.58351

0.46453

0.03018

0.46676

1.00000

0.69970

0.88697

0.79967

0.68070

0.67801

0.04449

0.63371

0.68070

0.51052

0.04070

0.53732

1.00000

0.75296

0.91497

0.84790

Table IV.11 DEPARTMENT OF SOCIAL WELFARE AND DEVELOPMENT, 1998 APPROPRIATIONS, ALLOTMENTS & OBLIGATIONS OFFICE OF THE SECRETARY (Central Office Only) As of September 30, 1998

Ratio of Allotments to Appropriations TOTAL

Ratio of Obligations to Appropriations TOTAL

Ratio of Obligations to Allotments TOTAL

A. PROGRAMS AND ACTIVITIES I. General Administration and Support a. General Administration and Support Services 1. General Management and Supervision b. Productivity Incentive Bonus

0.87231 1.00000

0.77259 1.00000

0.88569 1.00000

II. Support to Operations a. Policy formulation, Standard Setting, Program Devt, Social Research, International and Local Networking, and Technical Assistance 1. Family and Community Welfare 2. Child and Youth Welfare 3. Women's Welfare 4. Disabled Person's Welfare 5. Emergency Asistance

0.86734 0.67152 0.63824 0.88878 0.48790

0.82510 0.66774 0.63150 0.87694 0.48729

0.95131 0.99438 0.98945 0.98667 0.99873

0.45737

0.44158

0.96546

0.41824

0.41824

1.00000

0.63173 0.79948

0.54063 0.79818

0.85579 0.99837

TOTAL

0.75391

0.72485

0.96145

B. PROJECTS I. Locally-Funded Project(s) a. CIDSS in the Most Depressed Provs under SRA b. Sulong Dunong Para sa Kabataan c. Tulay 2000 d. Special Project for Poverty Mapping e. SEA-Kaunlaran II f. Family Welfare Fund

0.75086 0.75000 0.75000 0.75000 0.75000 0.75000

0.74976 0.74867 0.75000 0.66787 0.74580 0.16667

0.99853 0.99822 1.00000 0.89050 0.99440 0.22222

TOTAL

0.75080

0.74510

0.99241

GRAND TOTAL

0.75268

0.73283

0.97362

III. Operations a. Assistance Program for Distressed and Disadvantage Population 1. Nationwide Emergency Assistance\Calamity Relief Operations, etc.

2. Assistance to Persons with Disability including P15,000,000 for Senior Citizens 3. Protective Services for Children and Youth in Especially Difficult Circumstances c. Maintenance and Operations of Centers and Inst

Source: Department of Social Welfare and Development, Office of the Secretary

Table IV.12 PERCENTAGE CHANGE IN LOCALLY SOURCED REVENUE 1997-1998

RPT

1

GROWTH RATE (%) Other Tax Nontax

Total LSR

2

Ratio of Actual LSR to Estimated LSR

Province Bulacan Iloilo Misamis Oriental Southern Leyte

0.26 23.25 (1.70) (0.02)

(0.29) 2.46 3.21 (0.04)

0.26 5.30 (20.27) (0.10)

0.14 16.70 (19.01) (0.05)

100.00 125.61 71.43 80.50

Cities Antipolo Quezon Iloilo Cagayan de Oro Davao

(1.06) (5.31) 8.74 8.23 25.78

12.88 (5.02) 6.47 15.95 (12.47)

(58.93) (8.28) 12.37 8.42 26.56

(18.34) (5.50) 8.18 11.86 4.22

91.70 76.23 100.00 84.57 68.99

(14.24) (27.68) (7.99) 1.97 26.01 13.38 69.88 (6.97) (29.49) (22.39) (20.42)

11.70 5.58 (64.20) 25.41 15.43 25.09 9.95 (6.24) 8.56 29.00 30.38

(23.05) 19.92 (49.51) (8.70) 18.98 (7.23) (3.17) 37.96 25.75 29.25 19.70

(9.11) 11.84 (49.75) (1.22) 20.64 2.11 6.00 10.30 (0.91) 22.63 16.39

119.77 98.00 23.65 106.49 72.93 94.09 49.95 68.14 93.36 45.16 47.98

Municipalities San Jose del Monte, Bulacan Bauan, Batangas Banate, Iloilo Leon, Iloilo San Miguel, Iloilo Libagon, S. Leyte Padre Burgos, S. Leyte Tomas Oppus, S. Leyte Gitagum, Misamis Oriental Libertad, Misamis Oriental Opol, Misamis Oriental

Notes : 1/ RPT - Real Property Tax 2/ Locally Sourced Revenue Source: Local Government Units.

Table IV.13 EXPENDITURE SHARE BY SECTOR, APPROPRIATIONS VERSUS OBLIGATIONS GENERAL FUND (CURRENT ACCOUNT ONLY),1998

GENERAL SERVICES AppropriationsObligations

ECONOMIC SERVICES AppropriationsObligations

SOCIAL SERVICES AppropriationsObligations

HEALTH AppropriationsObligations

SOCIAL WELFARE AppropriationsObligations

Province Bulacan Iloilo Misamis Oriental Southern Leyte

35.57 40.70 22.23 20.54

35.57 46.64 23.35 22.22

19.65 26.95 33.31 30.47

19.65 29.39 38.90 26.81

39.26 15.34 28.64 35.71

39.26 16.79 28.34 38.85

25.19 5.97 20.22 34.95

25.19 7.01 21.03 38.11

2.62 0.54 1.97 0.63

2.62 0.64 1.93 0.64

Cities Antipolo Quezon Iloilo Cagayan de Oro Davao

38.33 46.97 38.38 29.97 41.76

40.96 43.42 48.79 31.28 46.56

17.42 5.15 21.72 21.73 19.70

17.42 6.01 12.67 20.09 13.42

24.86 28.59 29.29 37.28 18.46

24.94 31.44 28.10 37.92 19.70

8.09 4.58 9.64 13.34 7.28

8.22 4.50 12.39 14.63 7.67

1.35 1.85 3.83 1.91 2.09

1.33 1.77 4.91 2.19 2.05

Municipalities San Jose del Monte, Bulacan Bauan, Batangas Banate, Iloilo Leon, Iloilo San Miguel, Iloilo Libagon, S. Leyte Padre Burgos, S. Leyte Tomas Oppus, S. Leyte Gitagum, Misamis Oriental Libertad, Misamis Oriental Opol, Misamis Oriental

64.39 16.91 51.70 54.38 49.97 56.37 55.87 63.22 53.27 43.95 42.31

62.14 16.99 56.91 57.21 54.41 62.02 61.14 63.08 57.78 49.87 51.33

10.56 63.35 19.38 18.11 27.73 24.12 28.48 21.44 21.59 21.70 23.82

11.29 64.52 18.62 19.36 23.92 20.95 25.24 21.16 20.73 25.47 23.95

18.53 18.24 11.94 16.21 17.35 14.20 11.10 10.47 20.47 27.24 17.83

20.09 18.36 13.26 16.82 16.26 16.17 13.48 11.38 21.37 21.83 12.83

12.16 11.03 7.95 11.21 8.57 7.86 6.24 8.70 10.47 12.09 9.96

13.51 11.24 9.13 12.82 8.61 9.08 7.65 9.42 11.77 10.54 8.87

1.66 0.48 3.98 2.18 2.77 6.34 4.85 1.77 3.57 7.23 2.94

1.72 0.48 4.13 2.56 3.29 7.09 5.83 1.96 3.59 7.85 2.36

Source: Local Government Units

Table IV.14 REAL PER CAPITA LGU SPENDING, 1997-1998 CURRENT GENERAL FUNDS (in 1997 PRICES)

Province of Province of Province of Province of Quezon Bulacan Iloilo Misamis OrientalSouthern Leyte City

Antipolo City

Iloilo City

Cagayan de Oro Davao San Jose DM, Bauan, Banate, City City Bulacan Batangas Iloilo

Leon, San Miguel Libagon, Padre Burgos,Tomas Oppus, Gitagum, Iloilo Iloilo S. Leyte S. Leyte S. Leyte Misamis Or.

Libertad, Misamis Or.

Opol, Misamis Or.

TOTAL 1997 1998

285.38 260.83

132.50 135.67

472.94 492.12

491.28 458.28

1,574.93 1,370.35

333.09 445.77

1,071.06 986.84

1,235.90 1,201.87

1,401.75 1,242.01

352.23 307.07

1,861.36 1,980.51

570.93 390.58

544.31 424.51

595.51 568.95

848.33 846.85

923.06 922.31

657.33 730.33

717.21 739.79

833.63 537.59

569.43 633.36

1997 1998

112.73 129.67

77.27 83.24

332.73 324.02

328.76 330.65

541.50 489.53

133.36 144.15

571.65 558.55

665.20 636.95

426.08 378.94

145.81 154.63

616.19 710.10

434.72 280.22

324.30 328.07

486.25 459.29

629.91 677.20

659.58 764.63

471.43 490.02

513.43 531.61

690.62 454.77

429.55 474.02

1997 1998

145.13 127.40

27.02 20.06

116.07 92.85

83.62 119.32

814.83 697.33

132.58 188.25

430.71 418.84

388.31 382.09

797.41 780.74

122.03 97.26

1,027.62 1,133.98

133.87 110.36

79.32 66.48

107.75 109.65

114.26 117.45

188.00 138.04

173.12 196.72

164.45 197.89

122.53 76.95

127.17 139.43

1997 1998

27.52 3.76

28.21 32.38

24.14 75.26

78.89 8.31

218.60 183.50

73.15 113.37

68.70 9.45

182.40 182.84

178.26 82.34

84.39 55.19

217.54 136.43

2.34 -

140.69 29.95

1.52 -

104.15 52.21

75.48 19.65

12.78 43.59

39.32 10.28

20.49 5.87

12.71 19.93

1997 1998

81.29 92.77

59.28 63.27

103.54 114.93

111.20 101.82

725.11 594.97

147.32 182.60

503.57 481.47

471.85 375.89

680.57 578.32

243.20 190.82

309.36 336.41

375.29 222.29

364.64 242.87

329.51 309.55

553.88 525.21

522.27 563.95

432.68 460.72

426.52 427.45

395.35 268.11

326.35 325.09

32.31 39.23

14.67 13.02

10.57 18.00

9.42 10.32

284.29 267.28

44.96 70.12

131.01 129.85

122.18 100.96

384.83 342.17

76.50 50.09

58.93 64.98

59.58 41.05

39.92 33.13

41.53 32.25

43.20 37.86

49.97 25.02

73.46 73.67

53.69 52.02

24.08 19.58

52.07 19.68

60.91 51.25

45.65 39.87

188.54 191.44

178.26 122.88

84.11 82.36

58.70 77.65

132.40 125.04

255.47 241.44

266.26 166.64

43.17 34.67

1,230.73 1,277.85

86.35 72.74

66.83 82.16

149.04 136.11

166.66 177.42

149.49 232.76

130.94 154.54

134.68 153.36

199.35 136.94

132.64 151.70

24.70 33.18

8.89 3.95

28.55 17.59

30.67 43.30

30.07 24.48

9.55 6.25

41.06 34.13

34.71 46.67

111.64 80.93

25.76 16.77

888.19 965.71

10.74 11.02

15.53 18.35

29.50 28.84

61.02 68.84

37.53 90.84

89.69 86.10

25.38 64.64

9.17 8.94

25.46 29.45

125.96 102.40

20.83 22.78

123.47 139.45

171.59 178.05

405.00 430.86

111.86 111.17

324.22 277.28

245.00 455.81

274.18 244.64

54.73 61.69

318.24 363.55

61.55 51.79

81.58 71.42

111.10 92.49

121.54 136.94

97.76 124.31

91.36 83.07

155.04 158.10

200.39 117.33

109.89 81.23

73.27 42.68

2.00 1.11

19.56 10.95

18.03 16.56

190.08 190.19

56.86 37.54

147.77 151.80

72.90 125.65

153.73 140.03

13.54 15.36

77.48 100.61

16.52 14.54

23.86 13.82

30.85 17.79

3.79 3.45

22.44 20.88

7.63 4.95

84.42 80.36

84.39 42.55

49.09 14.95

65.28 65.70

7.30 9.50

112.35 103.47

167.61 174.66

64.94 61.67

35.43 36.65

124.45 122.25

196.69 175.81

95.46 95.26

39.21 41.49

214.66 222.51

46.68 35.67

57.34 54.43

59.99 48.97

66.76 76.89

50.74 70.52

75.51 68.78

71.78 87.09

105.16 56.65

81.52 56.19

21.38 11.73

0.52 0.19

16.13 7.92

17.01 16.20

10.81 15.12

15.60 14.56

43.05 43.59

50.84 45.59

36.24 39.35

6.77 7.20

55.39 71.89

11.29 10.04

10.25 7.47

10.37 3.62

2.23 2.43

2.44 0.54

4.81 2.91

11.96 21.97

31.88 3.69

31.51 3.06

25.08 21.94

5.32 5.65

35.98 35.05

76.88 83.70

64.94 60.67

20.35 20.47

91.01 90.73

98.93 93.25

72.84 68.06

33.88 36.66

45.41 50.95

46.68 35.67

48.69 47.84

50.33 47.02

66.76 76.89

50.74 70.52

75.51 68.78

65.02 68.58

75.86 54.88

81.52 56.19

9.39 2.39

0.52 0.19

2.16 1.71

6.52 7.29

10.81 15.05

12.23 11.85

9.61 12.07

28.61 24.97

18.42 15.85

5.44 5.71

5.46 8.76

11.29 10.04

1.74 0.88

0.71 1.67

2.23 2.43

2.44 0.54

4.81 2.91

5.20 3.47

2.58 1.92

31.51 3.06

5.76 6.85

0.85 0.87

10.14 9.52

3.52 2.93

25.57 24.27

6.89 5.95

57.03 48.45

19.69 26.30

27.29 25.51

3.27 5.29

5.18 9.46

14.87 16.12

11.43 10.79

20.03 18.74

54.78 60.05

47.02 53.79

15.86 14.30

39.44 26.54

53.99 42.19

13.48 14.93

1.71 2.44

0.28 0.28

2.76 2.26

1.02 0.35

4.23 4.51

2.07 1.58

32.05 24.56

4.25 12.35

16.34 16.29

2.46 2.82

3.11 4.17

5.23 4.50

0.80 0.78

0.90 0.48

1.56 1.03

20.00 20.35

2.82 2.04

28.64 13.92

31.76 26.26

5.93 1.76

Total PS

Total MOOE

Total CAPEX

Total GPS

GPS MOOE 1997 1998 Total Economic Services 1997 1998 Economic Services MOOE 1997 1998 Total Social Sector 1997 1998 Social Sector MOOE 1997 1998 Total Health Services 1997 1998 Health Services MOOE 1997 1998 Total Basic Health 1997 1998 Basic Health MOOE 1997 1998 Total Social Welfare 1997 1998 Social Welfare MOOE 1997 1998

Source: Local Government Units

TABLE V.1 LABOR FORCE PARTICIPATION RATE BY AGE GROUP, URBAN-RURAL, 1995-1999 1995 Q1

Philippines 64.27 15-19 years 35.50 20-24 years 67.63 25-34 year 73.45 35-44 years 77.05 45-54 years 77.96 55-64 years 69.19 65 years and over 41.91 Age not reported Urban 62.01 15-19 years 29.62 20-24 years 66.97 25-34 year 74.30 35-44 years 76.46 45-54 years 75.67 55-64 years 62.51 65 years and over 33.36 Age not reported Rural 66.59 15-19 years 41.38 20-24 years 68.48 25-34 year 72.49 35-44 years 77.64 45-54 years 80.22 55-64 years 75.29 65 years and over 49.12 Age not reported -

1996

1997

1998

1999

Q2

Q3

Q4

Ave

Q1

Q2

Q3

Q4

Ave

Q1

Q2

Q3

Q4

Ave

Q1

Q2

Q3

Q4

Ave

Q1

67.60 50.72 72.53 74.05 76.89 77.41 69.49 40.50 64.54 41.72 71.63 74.39 75.77 75.40 62.62 31.62 70.77 59.74 73.70 73.68 78.02 79.38 75.67 48.10 50.00

65.61 40.45 69.63 73.75 77.50 78.53 68.80 40.93 40.00 63.15 33.60 68.48 74.60 76.72 76.75 62.67 32.17 68.15 47.49 71.09 72.80 78.31 80.27 74.35 48.19 66.67

65.56 37.72 68.29 74.62 78.29 78.97 70.65 43.03 62.59 30.32 66.77 75.68 76.96 76.02 63.46 33.16 68.60 45.14 70.14 73.41 79.63 81.92 77.14 51.22 -

65.76 41.15 69.53 73.96 77.43 78.22 69.52 41.58 12.50 63.08 33.86 68.49 74.74 76.48 75.96 62.81 32.57 68.53 48.50 70.86 73.10 78.40 80.44 75.60 49.15 44.44

65.49 37.49 68.80 75.19 77.92 78.56 70.60 42.39 62.83 31.05 67.85 76.10 77.07 75.39 64.12 33.03 68.25 44.13 69.95 74.19 78.80 81.73 76.66 50.24 -

69.09 52.79 73.80 75.79 77.86 78.88 71.05 41.87 25.00 66.25 44.82 73.21 76.82 76.54 75.81 64.77 32.54 100.00 72.03 60.84 74.46 74.62 79.18 81.90 77.08 49.51 -

66.28 39.71 68.11 74.60 78.29 79.25 69.29 42.30 20.00 63.46 31.75 34.16 75.42 77.39 76.79 62.99 31.43 33.33 68.96 47.20 69.68 73.77 79.11 81.54 74.61 50.94 -

65.81 38.14 66.59 74.97 78.44 79.25 69.98 42.10 66.67 62.99 30.68 65.45 75.27 77.82 76.39 63.60 31.12 100.00 68.50 45.09 67.86 74.65 79.03 81.90 75.30 50.82 50.00

66.67 42.14 69.28 75.12 78.13 78.98 70.26 42.16 35.29 63.89 34.75 60.20 75.88 77.21 76.07 63.92 32.05 62.50 69.42 49.37 70.41 74.30 79.03 81.77 75.93 50.37 14.29

65.37 37.47 66.42 74.65 78.05 79.06 69.60 41.07 62.51 29.56 65.14 75.19 77.04 75.86 63.31 31.24 68.06 44.69 67.84 74.12 79.01 82.04 74.76 48.67 -

68.76 52.33 71.38 75.06 77.98 79.07 70.01 40.91 65.77 42.89 37.87 76.01 77.50 76.40 62.33 31.37 71.58 60.96 72.66 74.10 78.45 81.52 76.29 48.57 -

65.67 37.45 67.56 74.75 79.10 10.77 69.86 41.82 50.00 63.42 31.40 67.16 75.41 78.86 76.52 63.06 31.39 50.00 67.80 43.03 68.00 74.06 79.29 80.05 75.47 50.31 50.00

65.49 36.17 66.10 74.90 79.59 78.82 70.37 42.11 25.00 63.10 29.95 65.42 75.69 78.88 77.22 63.74 32.34 67.74 41.95 66.88 74.09 80.26 80.28 75.69 50.08 50.00

66.32 40.86 67.86 74.84 78.68 61.75 69.97 41.49 28.57 63.70 33.45 58.94 75.57 78.07 76.51 63.11 31.59 28.57 68.79 47.67 68.85 74.09 79.25 80.95 75.56 49.42 28.57

65.02 35.59 66.42 74.27 78.62 78.57 70.71 41.24 62.75 29.10 66.10 75.26 78.10 76.74 64.03 31.74 67.17 41.55 66.79 73.26 79.12 80.16 76.23 48.99 -

68.60 52.03 71.70 74.76 78.58 78.34 70.12 40.97 50.00 66.35 43.50 71.86 75.89 78.64 77.03 63.83 32.01 75.00 70.72 59.74 71.48 73.59 78.54 79.54 75.20 48.36 25.00

64.93 35.28 66.83 74.34 78.77 78.40 69.54 41.07 62.79 29.61 66.72 75.16 77.83 77.07 62.21 31.05 50.00 66.96 40.51 66.99 73.49 79.67 79.50 75.41 48.92 -

65.97 37.66 67.41 75.16 79.47 78.94 70.62 42.39 42.86 63.87 31.78 67.06 76.19 79.41 77.26 63.83 32.27 50.00 67.95 43.07 67.84 74.08 79.53 80.40 76.12 50.57 33.33

66.13 40.15 68.09 74.63 78.86 78.56 70.25 41.42 29.17 63.94 33.50 67.93 75.62 78.50 77.03 63.48 31.77 54.55 68.20 46.25 68.28 73.60 79.21 79.90 75.74 49.22 15.38

65.32 36.15 65.88 74.90 79.11 78.61 69.94 41.75 33.33 63.41 30.75 65.29 75.99 78.75 77.20 63.67 32.18 67.12 41.05 66.54 73.74 79.45 79.85 75.16 49.41 25.00

Source: Labor Force Survey, National Statistics Office

TABLE V.2 LABOR FORCE BY EMPLOYMENT STATUS, URBAN-RURAL, 1995-1998 1995 Q1 Labor Force Philippines Urban Rural Employed Philippines Urban Rural Unemployed Philippines Urban Rural Unemployment Rate Philippines Urban Rural Underemployment Rate Philippines Urban Rural Source: National Statistics Office

Q2

Q3

Q4

1996 Q1

Q2

Q3

Q4

1997 Q1

Q2

Q3

Q4

1998 Q1

Q2

Q3

Q4

1999 Q1

27619 29259 28602 28040 28924 30713 29657 29637 29631 31368 30154 30265 30240 32111 30593 31278 13530 14209 14027 13542 14129 14975 13841 13826 13738 14596 14145 14180 14212 15112 14363 14733 14089 15051 14574 14497 14795 15738 15816 15811 15893 16772 16009 16084 16027 16998 16230 16545

31168 14720 16448

25194 25724 26090 25698 26527 27358 27419 27442 27335 28105 27531 27888 27689 27837 27856 28262 11964 12103 12379 12045 12637 12883 12478 12505 12423 12748 12523 12688 12658 12790 12680 12947 13230 13621 13710 13652 13890 14475 14941 14937 14912 15357 15008 15200 15031 15046 15176 15315

28368 12963 15405

2425 1566 859

3535 2106 1430

2512 1648 864

2342 1497 845

2397 1492 905

3355 2092 1263

2238 1363 875

2195 1321 874

2296 1315 981

3263 1848 1415

2623 1622 1001

2377 1492 884

2551 1554 996

4274 2322 1952

2737 1683 1054

3016 1786 1230

2800 1757 1043

8.8 11.6 6.1

12.1 14.8 9.5

8.8 11.7 5.9

8.4 11.1 5.8

8.3 10.6 6.1

10.9 14.0 8.0

7.5 9.8 5.5

7.4 9.6 5.5

7.7 9.6 6.2

10.4 12.7 8.4

8.7 11.5 6.3

7.9 10.5 5.5

8.4 10.9 6.2

13.3 15.4 11.5

8.9 11.7 6.5

9.6 12.1 7.4

9.0 11.9 6.3

18.6 14.6 22.2

20.3 17.3 23.0

21.3 19.1 23.3

19.8 17.3 22.0

21.0 18.5 23.2

22.2 19.9 24.3

21.5 18.1 24.4

19.4 14.4 23.6

21.1 16.9 24.5

23.4 20.2 26.1

23.1 19.1 26.3

20.8 16.9 24.1

21.6 17.7 24.9

21.0 17.1 24.3

20.8 17.3 23.8

23.7 20.6 26.3

22.1 18.6 25.1

TABLE V.3 EMPLOYMENT BY MAJOR INDUSTRY GROUP (In Thousand Persons), 1991 - 1998 1991

1992

1993

1994

1995

1996

1997

1998

22,979

23,917

24,443

25,166

25,696

27,442

27,888

28,261

10,403

10,869

11,194

11,249

11,323

11,451

11,260

11,272

Industry Mining and Quarrying Manufacturing Electricity, Gas and Water Construction

3,686 150 2,391 99 1,046

3,816 143 2,546 92 1,035

3,793 130 2,455 106 1,102

3,970 101 2,582 100 1,187

4,008 95 2,571 103 1,239

4,567 115 2,756 123 1,573

4,659 124 2,755 139 1,641

4,442 104 2,687 140 1,511

Services Wholesale and Retail Transportation, Storage and Communication Financing, Insurance, Real Estate and Business Services Community, Social and Personal Sevices

8,891 3,172 1,143 451 4,116

9,231 3,283 1,221 452 4,254

9,457 3,415 1,359 496 4,174

9,947 3,563 1,402 494 4,480

10,365 3,745 1,489 551 4,559

11,424 4,062 1,657 681 5,019

11,969 4,219 1,769 680 5,296

12,547 4,328 1,885 695 5,631

9

21

13

8

21

5

5

8

Industry Group Total Agriculture, Fishery and Forestry

Not elsewhere classified

Source: October Rounds of the Labor Force Survey, National Statistics Office

TABLE V.4 EMPLOYED WORKERS BY AGE GROUP, URBAN-RURAL, January 1996 to October 1998 Area and Age Group

Jan-96

Apr-96

Jul-96

Oct-96

Jan-97

Apr-97

Jul-97

Oct-97

Jan-98

Apr-98

Jul-98

Oct-98

Philippines 15 - 19 20 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 years and over Age not reported

26,527 2,688 3,158 6,213 6,027 4,527 2,684 1,230 -

27,358 3,255 3,324 6,175 6,059 4,584 2,725 1,234 1

27,419 2,696 3,383 7,068 6,380 4,282 2,428 1,181 1

27,335 2,615 3,366 7,019 6,370 4,303 2,480 1,182 -

27,335 2,615 3,366 7,019 6,370 4,303 2,480 1,182 -

28,105 3,185 3,401 7,000 6,322 4,413 2,582 1,203 -

27,531 2,517 3,295 6,982 6,409 4,440 2,625 1,260 3

27,888 2,549 3,242 7,024 6,535 4,548 2,702 1,288 1

27,689 2,497 3,219 6,888 6,510 4,553 2,745 1,276 -

27,837 2,879 3,264 6,789 6,426 4,493 2,712 1,270 4

27,856 2,464 3,285 6,922 6,437 4,677 2,739 1,331 1

28,262 2,571 3,255 6,913 6,648 4,709 2,785 1,379 2

Urban 15 - 19 20 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 years and over Age not reported

12,637 1,042 1,650 3,249 2,938 2,158 1,169 432 -

12,883 1,193 1,694 3,236 2,956 2,172 1,202 430 1

12,478 964 1,665 3,486 3,023 1,963 997 379 1

12,423 912 1,658 3,470 3,023 1,961 1,008 391 -

12,423 912 1,658 3,470 3,023 1,961 1,008 391 -

12,748 1,099 1,679 3,512 3,006 2,019 1,025 408 -

12,523 899 1,631 3,478 3,041 1,997 1,058 418 2

12,688 930 1,602 3,484 3,076 2,081 1,073 443 -

12,658 886 1,621 3,441 3,078 2,076 1,112 443 -

12,790 986 1,651 3,434 3,072 2,099 1,101 446 3

12,680 909 1,631 3,462 3,041 2,127 1,072 437 1

12,947 941 1,642 3,502 3,173 2,109 1,113 467 1

Rural 15 - 19 20 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 years and over Age not reported

21,678 1,646 1,508 2,964 3,090 2,369 1,515 798 -

14,475 2,062 1,630 2,939 3,103 2,412 1,523 804 -

14,941 1,732 1,718 3,582 3,357 2,319 1,431 802 -

14,912 1,703 1,709 3,549 3,347 2,342 1,472 791 -

14,912 1,703 1,709 3,549 3,347 2,342 1,472 791 -

15,357 2,086 1,722 3,488 3,316 2,394 1,557 795 -

15,008 1,619 1,664 3,504 3,368 2,443 1,567 842 1

15,200 1,619 1,640 3,540 3,459 2,467 1,629 845 1

15,031 1,611 1,598 3,447 3,432 2,476 1,634 833 -

15,046 1,893 1,613 3,355 3,354 2,394 1,611 824 1

15,176 1,555 1,654 3,460 3,396 2,550 1,667 894 -

15,315 1,630 1,613 3,411 3,476 2,600 1,672 912 1

Source: Various Labor Force Survey rounds, National Statistics Office.

TABLE V.5 TOTAL EMPLOYED BY HIGHEST EDUCATIONAL ATTAINMENT, January 1996 - October 1998 Educational Attainment Total No Grade Completed Grade I to V Elementary Graduate 1st to 3rd Year High School Graduate College Undergraduate College Graduate Not Reported

Jan-96

Apr-96

Jul-96

Oct-96

Jan-97

Apr-97

Jul-97

Oct-97

Jan-98

Apr-98

Jul-98

Oct-98

26,527

27,358

27,419

27,442

27,335

28,105

27,531

27,888

27,689

27,837

27,856

28,262

844 5,099 5,966 3,467 5,467 2,730 2,911 43

822 5,060 6,061 3,785 5,687 2,910 2,988 54

934 5,385 5,970 3,540 5,430 2,966 3,129 65

884 5,306 5,998 3,478 5,498 2,963 3,266 50

892 5,220 5,968 3,495 5,471 2,966 3,257 65

903 5,285 5,893 3,876 5,571 3,260 3,250 67

858 5,382 5,860 3,605 5,585 3,095 3,079 67

870 5,335 6,064 3,636 5,713 3,062 3,128 79

859 5,262 5,966 3,622 5,663 3,065 3,160 92

812 5,123 5,865 3,818 5,777 3,243 3,110 88

820 5,233 5,915 3,684 5,724 3,145 3,267 69

844 5,312 5,907 3,760 5,881 3,125 3,347 85

Source: Various Labor Force Survey rounds, National Statistics Office.

TABLE V.6 DEPLOYED OVERSEAS FILIPINO WORKERS, 1991-1998

In Persons Workers Deployed Landbased Seabased Growth Rates (%) Workers Deployed Landbased Seabased

1991

1992

1993

1994

1995

1996

1997

1998

615,019 489,260 125,759

686,461 549,655 136,806

696,630 550,872 145,758

719,602 565,226 154,376

654,022 488,621 165,401

660,122 484,653 175,469

747,696 559,227 188,469

755,684 562,384 193,300

37.9 46.1 13.1

11.6 12.3 8.8

Source: Philippine Overseas Employment Administration

1.5 0.2 6.5

3.3 2.6 5.9

-9.1 -13.6 7.1

0.9 -0.8 6.1

13.3 15.4 7.4

1.1 0.6 2.6

TABLE V.7 DEPLOYED LANDBASED OVERSEAS FILIPINO WORKERS BY COUNTRY OF DESTINATION, 1991-1998

1991 Total Asia Hongkong Indonesia Japan Korea Malaysia Singapore Thailand Others Middle East Americas Europe Africa Oceania Trust Territories Unspecified

1992

1993

In Persons 1994 1995

1996

1997

1998

Growth Rates (%) 1992 1993 1994 1995 1996 1997 1998

489260 549655 550872 565226 488621 484653 559227 562344 12.3 0.2 2.6 -13.6 -0.8 15.4 132592 134776 168205 194120 166774 174308 235129 221257 1.6 24.8 15.4 -14.1 4.5 34.9 50652 52261 62583 62161 51701 43861 78513 64160 3.2 19.8 -0.7 -16.8 -15.2 79.0 639 760 812 922 1225 1497 2031 1625 18.9 6.8 13.5 32.9 22.2 35.7 57344 51949 43542 54879 25032 20183 33226 38122 -9.4 -16.2 26.0 -54.4 -19.4 64.6 193 230 703 5054 4395 2968 3647 2091 19.2 205.7 618.9 -13.0 -32.5 22.9 5741 7095 12409 11674 11622 12340 13581 4660 23.6 74.9 -5.9 -0.4 6.2 10.1 7697 8656 11568 11324 10736 15087 16055 13373 12.5 33.6 -2.1 -5.2 40.5 6.4 43 109 278 442 748 916 1269 1058 153.5 155.0 59.0 69.2 22.5 38.5 10283 13716 36310 47664 61315 77456 86807 96168 33.4 164.7 31.3 28.6 26.3 12.1 302825 340604 302975 286387 234310 221224 221047 226803 12.5 -11.0 -5.5 -18.2 -5.6 -0.1 13373 12319 12228 12603 13469 8378 7058 8210 -7.9 -0.7 3.1 6.9 -37.8 -15.8 13156 14590 13423 11513 10279 11409 12626 15682 10.9 -8.0 -14.2 -10.7 11.0 10.7 1964 2510 2425 3255 3615 2494 3517 5548 27.8 -3.4 34.2 11.1 -31.0 41.0 1374 1669 1507 1295 1398 1577 1970 2062 21.5 -9.7 -14.1 8.0 12.8 24.9 7380 11164 8890 8489 7039 4869 5280 6483 51.3 -20.4 -4.5 -17.1 -30.8 8.4 16596 32023 41219 47564 51737 60394 72600 76299 93.0 28.7 15.4 8.8 16.7 20.2

Source: Philippine Overseas Employment Administration

0.6 -5.9 -18.3 -20.0 14.7 -42.7 -65.7 -16.7 -16.6 10.8 2.6 16.3 24.2 57.7 4.7 22.8 5.1

TABLE V.8 REMITTANCES OF OVERSEAS FILIPINO WORKERS - BY DESTINATION, 1990-1998 (in Thousand US Dollar) YEAR Total Africa America Asia Europe Middle East Oceania Othera

1990 1203009 25 803235 75401 93053 105362 19714 106219

1991 1649374 18 1276295 89701 112868 104793 9097 56602

1992 2221788 6 1162823 112009 147932 152653 8036 638329

1993 2276395 1 1430656 172983 178470 173278 10866 310141

1994 3008117 10 1984888 388930 254364 131688 54614 193623

1995 3868378 0 2763188 462250 250490 41483 70638 280329

1996 1997 4306641 5741835 0 0 2579942 4127656 535959 454791 574062 436050 39188 25375 67873 19396 509617 678567

1998b 4461894 516 3592331 372090 304018 53030 14703 125206

Notes: Total amount of remittances of Overseas Filipino Workers from countries not elsewhere classified.

Thus, totals for the regions may be understated as there may be countries covered which are lumped under others. b January-November 1998 a

Source: Bangko Sentral ng Pilipinas

TABLE V.9 NUMBER OF FIRMS THAT CLOSED OR RETRENCHED DUE TO ECONOMIC REASONS Semestral Data, 1996-1998 Semester

Total

Closure

Retrenchment

Rotation, etc.

1st Sem 2nd Sem

1,079 614 599

347 146 211

724 455 372

39 20 23

1st Sem 2nd Sem

1,155 580 683

338 180 163

804 381 508

48 26 25

3,072

642

2,310

293

1st Sem

1,936

403

1,420

172

2nd Sem

1,725

254

1,378

169

1996

1997

1998

Source : Bureau of Labor and Employment Statistics - Figures may not add up to total due to multiple reporting

TABLE V.10 NUMBER OF FIRMS THAT CLOSED OR RETRENCHED DUE TO ECONOMIC REASONS Regional Annual Data, 1996 -1998 Region

1996

1997

1998

1,077

1,155

3,072

NCR

610

575

1,708

CAR 1 - Ilocos Region 2 - Cagayan Valley 3 - Central Luzon 4 - Southern Tagalog 5 - Bicol Region 6 - Western Visayas 7 - Central visayas 8 - Eastern Visayas 9 - Western Mindanao 10 - Northern Mindanao 11 - Southern Mindanao 12 - Central Mindanao CARAGA

10 15 8 48 52 8 48 140 0 6 27 96 0 9

12 21 5 60 99 25 72 115 13 9 37 98 14 0

16 40 21 155 192 26 186 268 32 18 108 257 26 19

Philippines

Source : Bureau of Labor and Employment Statistics

TALBE V.11 NUMBER OF FIRMS THAT CLOSED OR RETRENCHED DUE TO ECONOMIC REASONS

BY SECTOR, Annual Data, 1996-1998 Industry

1996

1997

1998

1,077

1,155

3,072

Agricultural. Fishery and Forestry

97

70

95

Industry Mining Manufacturing Electricity, Gas and Water Construction

545 14 508 2 21

568 23 505 9 31

1,254 48 1,025 8 173

Services Wholesale and Retail Trade Transportation , Storage and Comm.

Financing, Insurance, R. Estate and Business Services Community, Social and Personal Services

435 134 68 93

517 167 91 130

1,723 600 257 491

140

129

375

All Industries

Source : Bureau of Labor and Employment Statistics

TABLE V.12 NUMBER OF WORKERS AFFECTED BY THE CRISIS, PHILIPPINES, 1995-1998

MONTH Total January February March April May June July August September October November December

Total 66,060 3,156 4,050 2,945 3,556 2,483 3,422 5,929 5,681 2,547 11,385 4,681 16,225

1995 Permanent Temporary Rotation, etc.

37,980 2,075 1,745 1,683 2,970 1,739 2,239 1,821 2,709 1,443 8,955 3,414 7,187

19,265 503 1,478 905 174 332 836 1,373 2,039 627 1,511 650 8,837

8,815 80,701 578 7,324 827 4,664 357 8,720 412 6,003 412 7,303 347 6,309 2,735 8,292 933 10,759 477 4,853 919 5,930 617 3,554 201 6,990

Source: Bureau of Labor and Employment Statistics (BLES)

Permanent Temporary Rotation, etc.

Total

complete and total separation of workers from employment. separation of workers not more than six (6) months. rotation of work, reduce of working time.

1996 Permanent Temporary Rotation, etc.

47,008 3,783 2,955 7,282 3,940 2,590 2,081 5,000 7,050 3,579 2,902 2,661 3,185

29,487 2,557 1,353 1,338 1,879 4,641 4,147 3,074 2,949 638 2,213 893 3,805

Total

4,206 62,724 984 5,093 356 3,400 100 7,357 184 4,218 72 7,988 81 5,059 218 5,099 760 2,988 636 3,760 815 4,243 0 6,042 0 7,477

1997 Permanent Temporary Rotation, etc.

39,176 4,337 1,991 5,875 3,553 4,111 1,596 2,638 2,175 2,440 2,914 3,397 4,149

19,843 671 734 1,191 364 3,603 3,210 2,113 737 974 704 2,466 3,076

Total

3,705 155,198 85 15,568 675 17,046 291 19,577 301 10,434 274 9,218 253 12,009 348 16,114 76 16,146 346 12,958 625 12,849 179 8,397 252 4,882

1998 Permanent Temporary Rotation, etc.

76,726 6,428 7,844 8,572 6,091 6,230 4,758 8,820 7,627 5,885 6,923 4,426 3,122

50,744 7,387 5,700 7,652 2,717 1,287 4,699 4,806 4,839 4,700 4,293 1,762 902

27,728 1,753 3,502 3,353 1,626 1,701 2,552 2,488 3,680 2,373 1,633 2,209 858

TABLE V.13 IMPACT OF THE CRISIS AND EL NIﾃ前 ON EMPLOYMENT AND LABOR MARKET, JANUARY 1999 (Percent of Communities) Impact No Effect Retrenchment Closure Large Scale Unemplyment Slack demand for laborers (esp. construction workers) Longer working hours Job rotation Contractualization Below Minimum Wage Employment Reduced business operation

Middle income 15 39 31 8 15

Urban Poor 43 14 29 43

50 13

8 31 8 15

57 14 57 14

13 25 13 13

8

29

13

Source :Social Impact of the Regional Financial Crisis, 1999 Focus Group Discussions

Fishing

13

Farming 18 23 9 9 5 9 5 5

TABLE V.14 PERCENT DISTRIBUTION OF PERSONS 15 YEARS OLD AND OVER

BY OCCUPATION, BY SEX, ALL COMMUNITIES Occupation

Total

Male

Female

Total

Male

Female

All Occupation

100.0

100.0

100.0

100.0

49.3

50.7

Professional

3.7 1.8 3.1 5.9

3.0 3.1 2.7 3.8

4.5 0.5 3.4 7.9

100.0 100.0 100.0 100.0

39.3 85.2 43.5 31.8

60.7 14.8 56.5 68.2

6.3

4.1

8.4

100.0

31.9

68.1

13.1

22.6

3.9

100.0

84.8

15.2

12.6 7.5 46.1

22.8 6.6 31.4

2.6 8.4 60.4

100.0 100.0 100.0

89.4 43.4 33.5

10.6 56.6 66.5

Administrative,executive Clerk, office worker Sales worker Beautician, barber, service worker, inc. household help Factory worker, driver, carpenter, laborer and related workers Farmer, fisherman and related worker Others Not Gainfully Employed

Source: Labor Force Survey, National Statistics Office

TABLE V.15 DISTRIBUTION OF PERSONS 15 YEARS AND OVER, JANUARY 1999

BY OCCUPATION, SEX AND TYPE OF COMMUNITY Occupation and Sex

Commercial Upland Sustenance Fishing

Middle Income

Urban Poor

100.0 47.4 52.6

100.0 47.5 52.5

100.0 50.6 49.4

100.0 52.3 47.7

100.0 50.8 49.2

100.0 54.5 45.5

2.6 83.3 16.7

0.5 100.0 -

4.0 60.0 40.0

1.5 66.7 33.3

8.3 51.9 48.1

3.0 66.7 33.3

0.4 100.0 -

1.0 100.0

0.8 100.0

0.5 100.0

5.2 5.9 94.1

1.3 50.0 50.0

2.6 33.3 66.7

1.5 100.0 -

3.2 75.0 25.0

1.0 50.0 50.0

6.5 52.4 47.6

2.0 50.0 50.0

3.1 100.0 -

3.0 66.7 33.3

3.2 25.0 75.0

6.2 75.0 25.0

7.7 56.0 44.0

9.9 80.0 20.0

Beautician, barber, service worker, inc. household help Female Male

6.1 57.1 42.9

5.5 81.8 18.2

4.0 20.0 80.0

7.7 66.7 33.3

6.8 72.7 27.3

7.3 86.4 13.6

Factory worker, driver, carpenter, laborer and related worker Female Male

11.8 22.2 77.8

6.0 16.7 83.3

10.0 24.0 76.0

13.3 34.6 65.4

15.4 8.0 92.0

18.8 5.3 94.7

Farmer, fisherman and related worker Female Male

19.7 17.8 82.2

30.5 6.6 93.4

17.1 11.6 88.4

16.4 3.1 96.9

0.6 100.0

2.0 33.3 66.7

Others, n.e.c.

Female Male

8.3 47.4 52.6

7.5 80.0 20.0

7.2 55.6 44.4

9.2 72.2 27.8

4.0 53.8 46.2

9.9 43.3 56.7

Not gainfully employed Female Male

45.2 60.2 39.8

44.5 67.4 32.6

50.6 70.9 29.1

44.1 66.3 33.7

45.5 66.2 33.8

45.9 66.9 33.1

All Occupation Female Male Professional Female Male Administrative, executive Female Male Clerk, office worker Female Male Sales worker Female Male

Source: Social Impact of the Regional Financial Crisis Household Survey

TABLE V.16 REASONS FOR NOT WORKING, JANUARY 1999 ALL COMMUNITIES Reason All Reasons Change of residence Lack of capital No opportunity available Not looking for work/laziness Others Retrenched/dismissed/closure Seasonal/farm not ready for planting Source: Social Impact of the Regional Financial Crisis Household Survey

Percent 100.0 5.5 4.4 8.8 12.1 50.5 17.6 1.1

Table V.17 Impact of the Financial Crisis on Income of Households

by Decile, 1998 Decile

Percent Change in Income

1 2 3 4 5 6 7 8 9 10

-7.28 -7.08 -6.82 -6.65 -6.30 -5.87 -5.50 -5.06 -4.88 -4.64

Source: National Statistics Office.

Table V.18. Comparative Per Capita Income Using 1997 FIES and 1998 APIS

Nominal Real

1997 FIES 24,840 19,909

Source: National Statistics Office.

1998 APIS 23,949 17,494

Growth Rate (3.6) (12.1)

TABLE V.19 COMPARATIVE ANNUAL INCOME PER FAMILY USING the APIS and 1997 FIES,

BY INCOME DECILE 1997 Family Income and Expenditure Survey

1998 Annual Poverty Indicator Survey

Percentage Change 1997-1998

PHILIPPINES

123,008

121,438

(1.28)

First Decile Second Decile Third Decile Fourth Decile Fifth Decile Sixth Decile Seventh Decile Eight Decile Ninth Decile Tenth Decile

20,659 33,064 42,611 53,101 66,291 83,224 106,919 141,394 199,891 482,927

14,644 26,852 36,689 47,211 60,176 76,641 100,170 135,051 196,018 520,928

(29.12) (18.79) (13.90) (11.09) (9.22) (7.91) (6.31) (4.49) (1.94) 7.87

Income Decile

Sources: FIES, 1997 and APIS, 1998 of the National Statistics Office.

TABLE V.20 INFLATION RATE BY MAJOR COMMODITY GROUP, 1991 - 1998 (In Percent, 1988 = 100) Commodity Group

1991

1992

1993

1994

1995

1996

1997

1998

All Items

18.71

8.95

7.56

9.06

8.10

8.40

5.02

9.01

Food, Beverages and Tobacco Food Beverages Tobacco

15.35 14.84 23.35 18.79

6.83 6.58 14.20 3.00

6.11 6.02 6.29 7.94

8.27 8.64 3.16 6.14

9.53 9.93 5.79 4.12

9.88 10.14 8.14 5.16

1.93 1.75 2.19 6.79

7.75 6.42 2.62 9.75

23.41 16.93 (26.18) 27.41 32.51 16.23

11.62 10.77 17.57 5.71 7.13 13.36

9.43 7.39 12.63 7.59 7.84 8.04

10.04 4.79 13.08 6.92 8.82 10.97

6.36 3.33 10.66 2.99 6.51 0.91

6.56 3.56 9.53 6.60 9.51 (3.82)

9.06 3.81 9.66 8.23 13.24 1.99

9.43 5.71 10.64 7.97 14.29 7.10

Non-Food Clothing Housing and Repairs Fuel, Light and Water Services Miscellaneous

Source: National Statistics Office.

TABLE V.21 INFLATION RATE BY REGION, 1991 - 1998 (In Percent, 1988 = 100) Region Philippines NCR CAR Ilocos Cagayan Valley Central Luzon Southern Tagalog Bicol Western Visayas Central Visayas Eastern Visayas Western Mindanao Northern Mindanao Southern Mindanao Central Mindanao ARMM

Source: National Statistics Office.

1990

1991

1992

1993

1994

1995

1996

1997

1998

128.08

18.71

8.95

7.56

9.06

8.10

8.40

5.02

9.01

127.30 129.37 128.48 127.71 124.49 129.08 132.86 131.88 134.48 125.68 129.25 126.33 120.56 129.62 -

20.66 15.72 16.17 15.51 20.63 19.15 16.46 19.04 21.86 18.23 18.05 15.49 14.49 18.19 -

12.17 6.57 7.46 10.86 7.51 7.32 7.06 6.10 8.06 9.24 6.96 9.15 9.26 9.02 -

10.50 6.99 10.88 7.83 5.54 5.88 7.60 8.34 6.38 6.75 6.79 5.60 4.70 5.96 -

10.19 11.68 8.48 5.63 9.98 9.01 8.22 7.13 8.03 9.36 9.23 9.29 8.66 7.87 -

8.10 7.94 8.41 6.52 6.60 7.88 10.68 9.11 6.98 9.84 7.14 7.93 8.10 5.32 -

8.33 7.29 8.94 9.09 7.96 8.58 9.92 7.63 7.54 9.70 10.86 7.90 7.53 7.64 9.33

6.59 2.09 2.91 3.79 6.01 5.82 2.38 3.99 5.13 1.59 2.75 4.18 4.17 4.90 7.77

9.32 8.54 9.64 8.88 8.88 9.40 8.13 7.60 7.54 8.23 9.59 9.38 12.39 7.41 13.72

TABLE V.22 CHANGES IN HOUSEHOLD CONSUMPTION AND EXPENDITURES, ALL COMMUNITIES, JANUARY 1999 (Continuation) Item

Percent of Total Respondents

Item

Percent of Total Respondents

Changes in number of full meals Stop consuming some good High prices Not available Lost interest Others

41.6 93.3 2.2 0.6 3.9

One in '97 and now Two in '97 One now Two now Three now Three in '97 Two now Three now Irregular now Irregular in '97 and now No reply

0.2 3.7 6.3 75.0 18.8 93.5 1.2 98.3 0.5 0.2 2.3

When reduced All times Since last month About 6 months ago About a year Over a year

100.0 6.7 6.7 33.3 53.3

Changes in Household Expenditures Dining out not aware no change increase at most 10% up to 25% up to 50% Decreased at most 10% up to 25% up to 50% up to 75% over 75% no reply

100.0 23.0 37.2 9.3 52.5 25.0 22.5 17.7 14.5 19.7 30.3 14.5 21.1 12.8

Food prepared at home not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% up to 25% up to 50% no reply

100.0 1.2 34.9 42.3 39.0 33.5 22.5 4.9 17.7 27.6 40.8 31.6 4.0

Children's clothing not aware no change increase at most 5% up to 10% up to 25% up to 50% Decreased at most 10% up to 25% up to 50% over 50% no reply

100.0 6.0 35.1 28.8 23.4 40.3 22.6 13.7 18.6 23.8 20.0 38.8 17.5 11.4

Adults' clothing not aware no change increase at most 5% up to 10% up to 25% up to 50% Decreased at most 10% up to 25% up to 50% over 50% no reply

100.0 4.4 44.9 22.3 28.1 43.8 17.7 10.4 20.5 23.9 15.9 35.2 25.0 7.9

TABLE V.22 CHANGES IN HOUSEHOLD CONSUMPTION AND EXPENDITURES, ALL COMMUNITIES, JANUARY 1999 (Continuation) Item

Percent of Total Respondents

Children's transportation not aware no change increase at most 5% up to 10% up to 25% over 25% Decreased at most 10% up to 25% over 25% no reply

100.0 12.6 29.5 34.0 20.5 28.8 38.4 12.3 3.3 35.7 14.3 50.0 20.7

School fees and related expenses not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 20% over 20% no reply

100.0 12.1 16.3 48.1 38.6 42.5 16.4 2.4 3.0 61.5 38.5 20.5

Utilities

100.0

not aware no change increase at most 5% up to 10% up to 25% up to 50% over 50% Decreased at most 10% over 10% no reply

3.5 24.0 62.1 15.0 40.8 27.7 11.6 4.9 2.8 58.3 41.7 7.7

Item Others' transportation not aware no change increase at most 5% up to 10% up to 25% over 25% Decreased at most 10% up to 25% over 25% no reply Medical expenses

Percent of Total Respondents 100.0 9.3 23.0 29.5 21.3 33.1 37.8 7.9 3.5 46.7 13.3 40.0 34.7

not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% up to 50% over 50% no reply

100.0 5.6 25.3 55.1 38.8 39.7 17.3 4.2 6.0 50.0 38.5 11.5 7.9

House rent, repair & maintenance not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% over 10% no reply

100.0 11.2 47.2 25.1 41.7 30.6 20.4 7.4 1.4 66.7 33.3 15.1

TABLE V.22 CHANGES IN HOUSEHOLD CONSUMPTION AND EXPENDITURES, ALL COMMUNITIES, JANUARY 1999 (Continuation) Item Leisure not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% up to 50% over 50% no reply

Percent of Total Respondents 100.0 17.9 39.8 11.2 45.8 33.3 12.5 8.3 13.7 20.3 47.5 32.2 17.4 1997

Food Education Medical Clothing Transportation Housing Leisure

46.3 10.0 7.9 7.0 7.2 5.0 2.8

Item Gambling not aware no change increase at most 20% over 20% Decreased at most 10% up to 50% over 50% no reply

1998 47.3 10.3 8.1 5.9 7.3 5.2 2.1

Source : Social Impact of the Regional Financial Crisis, Household Survey.

Percent of Total Respondents 100.0 38.1 23.7 4.4 57.9 42.1 7.4 40.6 18.8 40.6 26.3

TABLE V.23 CHANGES IN HOUSEHOLD CONSUMPTION AND EXPENDITURES

BY TYPE OF COMMUNITY, JANUARY 1999 (Percent of Total Household Respondents) Item

Middle Income

Commercial

Upland

Sustenance

Fishing

25.0 93.3 6.7

40.0 95.8 4.2

48.3 79.3 10.3 10.3

45.8 88.9 3.7 3.7 3.7

38.6 100.0 -

50.0 97.8 2.2

Changes in number of full meals All Meals One in '97 and Now Two in'97 One Now Two Now Three Now Three in '97 Two Now Three Now Irregular Now Irregular in '97 and Now no reply

100.0 5.0 33.3 66.7 90.0 100.0 5.0

100.0 1.7 8.3 100.0 83.3 100.0 6.7

100.0 98.3 100.0 1.7

100.0 3.4 50.0 50.0 94.9 100.0 1.7

100.0 1.0 100.0 99.0 2.0 96.0 2.0 -

100.0 4.5 100.0 93.3 3.6 96.4 1.1 1.1

Changes in Household Expenditures Dining out not aware no change increase at most 10% up to 25% up to 50% Decreased at most 10% up to 25% up to 50% up to 75% over 75% no reply

100.0 23.3 35.0 15.0 66.7 22.2 11.1 5.0 33.3 33.3 33.3 21.7

100.0 31.7 33.3 8.3 40.0 40.0 20.0 10.0 66.7 16.7 16.7 16.7

100.0 26.7 28.3 16.7 60.0 20.0 20.0 18.3 18.2 45.5 27.3 9.1 10.0

100.0 37.3 39.0 1.7 100.0 10.2 16.7 50.0 16.7 16.7 11.9

100.0 14.9 39.6 8.9 44.4 22.2 33.3 30.7 19.4 22.6 32.3 19.4 6.5 5.9

100.0 14.4 43.3 6.7 50.0 16.7 33.3 21.1 5.3 21.1 15.8 57.9 14.4

Food prepared at home not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% up to 25% up to 50% no reply

100.0 1.7 33.3 40.0 50.0 33.3 16.7 20.0 58.3 16.7 25.0 5.0

100.0 5.0 25.0 45.0 29.6 48.1 14.8 7.4 18.3 18.2 45.5 36.4 6.7

100.0 20.0 60.0 36.1 22.2 36.1 5.6 18.3 18.2 63.6 18.2 1.7

100.0 25.4 47.5 35.7 32.1 14.3 17.9 27.1 18.8 50.0 31.3 -

100.0 53.5 31.7 43.8 37.5 18.8 11.9 16.7 33.3 50.0 3.0

100.0 1.1 37.8 38.9 40.0 31.4 28.6 15.6 35.7 35.7 28.6 6.7

Stop consuming some goods reasons: High prices Not available Lost interest Others

Urban Poor

TABLE V.23 CHANGES IN HOUSEHOLD CONSUMPTION AND EXPENDITURES

BY TYPE OF COMMUNITY, JANUARY 1999 (Percent of Total Household Respondents) Item

Middle Income

Commercial

Upland

Sustenance

Fishing

Urban Poor

Children's clothing not aware no change increase at most 5% up to 10% up to 25% up to 50% Decreased at most 10% up to 25% up to 50% over 50% no reply

100.0 5.0 33.3 33.3 30.0 25.0 25.0 20.0 13.3 25.0 50.0 12.5 12.5 15.0

100.0 13.3 26.7 23.3 35.7 50.0 14.3 26.7 25.0 18.8 37.5 18.8 10.0

100.0 8.3 30.0 31.7 21.1 36.8 36.8 5.3 25.0 20.0 26.7 53.3 5.0

100.0 3.4 37.3 30.5 22.2 33.3 11.1 33.3 25.4 20.0 66.7 13.3 3.4

100.0 5.0 41.6 26.7 18.5 40.7 29.6 11.1 13.9 14.3 28.6 28.6 28.6 12.9

100.0 3.3 36.7 28.9 19.2 53.8 15.4 11.5 13.3 41.7 8.3 16.7 33.3 17.8

Adult's clothing not aware no change increase at most 5% up to 10% up to 25% up to 50% Decreased at most 10% up to 25% up to 50% over 50% no reply

100.0 3.3 38.3 28.3 35.3 23.5 23.5 17.6 16.7 50.0 30.0 10.0 10.0 13.3

100.0 11.7 31.7 21.7 23.1 61.5 15.4 28.3 23.5 17.6 23.5 35.3 6.7

100.0 6.7 31.7 36.7 27.3 45.5 22.7 4.5 23.3 21.4 7.1 50.0 21.4 1.7

100.0 52.5 20.3 41.7 33.3 25.0 27.1 12.5 12.5 75.0 -

100.0 3.0 61.4 9.9 30.0 50.0 10.0 10.0 15.8 12.5 25.0 25.0 37.5 9.9

100.0 3.3 43.3 24.4 18.2 50.0 9.1 22.7 16.7 33.3 6.7 20.0 40.0 12.2

Transportation for children not aware no change increase at most 5% up to 10% up to 25% over 25% Decreased at most 10% up to 25% over 25% no reply

100.0 11.7 30.0 30.0 33.3 33.3 33.3 28.3

100.0 18.3 33.3 28.3 11.8 11.8 76.5 1.7 100.0 18.3

100.0 21.7 13.3 45.0 22.2 29.6 40.7 7.4 10.0 50.0 16.7 33.3 10.0

100.0 8.5 44.1 40.7 4.2 37.5 41.7 16.7 5.1 33.3 66.7 1.7

100.0 11.9 23.8 32.7 21.2 27.3 27.3 24.2 2.0 50.0 50.0 29.7

100.0 6.7 34.4 30.0 29.6 29.6 25.9 14.8 2.2 100.0 26.7

TABLE V.23 CHANGES IN HOUSEHOLD CONSUMPTION AND EXPENDITURES

BY TYPE OF COMMUNITY, JANUARY 1999 (Percent of Total Household Respondents) Item

Middle Income

Commercial

Upland

Sustenance

Fishing

100.0 5.0 31.7 23.3 35.7 28.6 28.6 7.1 1.7 100.0 38.3

100.0 11.7 31.7 21.7 23.1 15.4 46.2 15.4 5.0 66.7 33.3 30.0

100.0 18.3 21.7 40.0 16.7 45.8 37.5 3.3 50.0 50.0 16.7

100.0 5.1 30.5 30.5 33.3 27.8 38.9 5.1 33.3 66.7 28.8

100.0 6.9 11.9 33.7 11.8 23.5 44.1 20.6 3.0 66.7 33.3 44.6

100.0 10.0 20.0 26.7 20.8 50.0 29.2 3.3 66.7 33.3 40.0

School fees and related expenses not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 20% over 20% no reply

100.0 10.0 23.3 40.0 33.3 45.8 20.8 3.3 50.0 50.0 23.3

100.0 13.3 23.3 35.0 57.1 28.6 14.3 8.3 80.0 20.0 20.0

100.0 16.7 20.0 51.7 29.0 58.1 12.9 1.7 100.0 10.0

100.0 10.2 15.3 67.8 35.0 52.5 10.0 2.5 3.4 100.0 3.4

100.0 13.9 7.9 47.5 27.1 41.7 25.0 6.3 2.0 100.0 28.7

100.0 8.9 14.4 47.8 55.8 27.9 14.0 2.3 1.1 100.0 27.8

Medical expenses including medicine not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% up to 50% over 50% no reply

100.0 5.0 21.7 53.3 37.5 37.5 15.6 9.4 6.7 75.0 25.0 13.3

100.0 16.7 20.0 45.0 37.0 29.6 18.5 14.8 8.3 40.0 60.0 10.0

100.0 3.3 18.3 61.7 48.6 32.4 18.9 15.0 44.4 33.3 22.2 1.7

100.0 6.8 27.1 57.6 38.2 41.2 17.6 2.9 5.1 33.3 33.3 33.3 3.4

100.0 2.0 35.6 53.5 31.5 48.1 16.7 3.7 2.0 100.0 6.9

100.0 3.3 23.3 58.9 41.5 41.5 17.0 3.3 33.3 66.7 11.1

House rent, repair, maintenance not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% over 10% no reply

100.0 10.0 46.7 15.0 22.2 11.1 44.4 22.2 28.3

100.0 23.3 43.3 18.3 27.3 36.4 36.4 1.7 100.0 13.3

100.0 6.7 60.0 23.3 35.7 50.0 14.3 3.3 50.0 50.0 6.7

100.0 15.3 49.2 27.1 43.8 43.8 12.5 8.5

100.0 5.0 42.6 38.6 46.2 25.6 17.9 10.3 1.0 100.0 12.9

100.0 11.1 45.6 21.1 52.6 21.1 15.8 10.5 2.2 50.0 50.0 20.0

Transportation for others not aware no change increase at most 5% up to 10% up to 25% over 25% Decreased at most 10% up to 25% over 25% no reply

Urban Poor

TABLE V.23 CHANGES IN HOUSEHOLD CONSUMPTION AND EXPENDITURES

BY TYPE OF COMMUNITY, JANUARY 1999 (Percent of Total Household Respondents) Item

Middle Income

Commercial

Upland

Sustenance

Fishing

Utilities not aware no change increase at most 5% up to 10% up to 25% up to 50% over 50% Decreased at most 10% over 10% no reply

100.0 3.3 20.0 63.3 13.2 34.2 26.3 15.8 10.5 1.7 100.0 11.7

100.0 6.7 40.0 40.0 29.2 25.0 25.0 16.7 4.2 3.3 100.0 10.0

100.0 1.7 23.3 71.7 23.3 34.9 25.6 14.0 2.3 1.7 100.0 1.7

100.0 3.4 27.1 66.1 10.3 53.8 23.1 7.7 5.1 3.4 100.0 -

100.0 3.0 17.8 67.3 5.9 47.1 30.9 10.3 5.9 3.0 100.0 8.9

100.0 3.3 21.1 61.1 18.2 40.0 30.9 9.1 1.8 3.3 66.7 33.3 11.1

Leisure not aware no change increase at most 10% up to 25% up to 50% over 50% Decreased at most 10% up to 50% over 50% no reply

100.0 18.3 36.7 5.0 66.7 33.3 10.0 16.7 66.7 16.7 30.0

100.0 28.3 45.0 6.7 75.0 25.0 1.7 100.0 18.3

100.0 13.3 55.0 11.7 42.9 57.1 15.0 22.2 44.4 33.3 5.0

100.0 32.2 35.6 3.4 100.0 22.0 15.4 46.2 38.5 6.8

100.0 7.9 34.7 19.8 45.0 30.0 15.0 10.0 18.8 26.3 47.4 26.3 18.8

100.0 15.6 36.7 13.3 50.0 16.7 25.0 8.3 12.2 18.2 36.4 45.5 22.2

Gambling not aware no change increase at most 20% over 20% Decreased at most 10% up to 50% over 50% no reply

100.0 38.3 23.3 1.7 100.0 1.7 100.0 35.0

100.0 40.0 25.0 3.3 50.0 50.0 6.7 75.0 25.0 25.0

100.0 40.0 41.7 5.0 66.7 33.3 3.3 100.0 10.0

100.0 52.5 23.7 3.4 100.0 10.2 16.7 16.7 66.7 10.2

100.0 36.6 14.9 5.0 80.0 20.0 3.0 33.3 66.7 40.6

100.0 27.8 21.1 6.7 33.3 66.7 17.8 37.5 12.5 50.0 26.7

Source : Social Impact of the Regional Financial Crisis, Household Survey.

Urban Poor

Table V.24 COMPARATIVE AVERAGE MONTHLY INCOME USING THE APIS and 1997 FIES, BY INCOME DECILE

Income Decile

1997 Family Income and Expenditure Survey Value Percent (In P1,000)

1998 Annual Poverty Indicator Survey Value Percent (In P1,000)

PHILIPPINES

145,482,668

100.0

145,429,030

100.0

First Decile Second Decile Third Decile Fourth Decile Fifth Decile Sixth Decile Seventh Decile Eight Decile Ninth Decile Tenth Decile

2,443,310 3,910,487 5,039,661 6,280,286 7,840,237 9,843,010 12,645,437 16,722,746 23,641,295 57,116,200

1.7 2.7 3.5 4.3 5.4 6.8 8.7 11.5 16.3 39.3

1,753,661 3,215,663 4,393,773 5,653,844 7,206,445 9,178,194 11,995,918 16,173,106 23,474,261 62,384,166

1.2 2.2 3.0 3.9 5.0 6.3 8.2 11.1 16.1 42.9

Source: National Statistics Office.

TABLE V.25 IMMUNIZATION PROGRAM PERFORMANCE, 1996-1998

Province/City

1996 1997 1998 No. of % of No. of % of No. of % of % Change, Number % Change, Proportion Eligible immunized Eligible Eligible immunized Eligible Eligible immunized Eligible Population population Pop'n. Population population Pop'n. Population population Pop'n. 1996-1997 1997-1998 1996-1997 1997-1998

NCR 1s Dist. Mun. Manila 2nd Dist. Mun. Quezon City 3rd Dist. Mun. Caloocan City 4th Dist Mun. Pasay City

31,734 49,951 39,506 61,676 27,275 32,426 38,295 12,499

27,752 48,774 38,704 67,407 21,124 28,414 32,115 12,056

87.5 97.6 98.0 109.3 77.4 87.6 83.9 96.5

33,116 50,260 41,142 63,736 27,702 34,255 40,597 12,744

31,122 49,682 40,206 63,207 24,755 30,915 36,319 11,618

94.0 98.8 97.7 99.2 89.4 90.3 89.5 91.2

34,559 50,572 42,859 65,865 28,138 36,187 43,041 12,993

31,283 49,874 41,009 60,131 26,770 34,789 39,607 11,952

90.5 98.6 95.7 91.3 95.1 96.1 92.0 92.0

12.1 1.9 3.9 -6.2 17.2 8.8 13.1 -3.6

0.5 0.4 2.0 -4.9 8.1 12.5 9.1 2.9

7.4 1.2 -0.3 -9.2 15.5 3.1 6.7 -5.5

-3.7 -0.2 -2.0 -8.0 6.4 6.4 2.8 0.9

NCR

293,362

276,346

94.2

303,551

287,824

94.8

314,214

295,415

94.0

4.2

2.6

0.6

-0.8

5,944 2,564 9,479 4,501 4,727 4,008 7,085

5,273 2,257 8,914 4,546 3,927 3,179 6,472

88.7 88.0 94.0 101.0 83.1 79.3 91.3

6,010 2,618 9,543 4,514 4,833 4,096 7,375

4,899 2,184 9,042 4,020 4,044 3,009 6,703

81.5 83.4 94.7 89.1 83.7 73.5 90.9

6,077 2,674 9,608 4,527 4,941 4,185 7,676

5,243 2,459 9,346 3,794 3,481 2,959 7,109

86.3 91.9 97.3 83.8 70.5 70.7 92.6

-7.1 -3.2 1.4 -11.6 3.0 -5.3 3.6

7.0 12.6 3.4 -5.6 -13.9 -1.7 6.1

-8.1 -5.2 0.7 -11.8 0.7 -7.3 -0.4

5.9 10.2 2.7 -5.9 -15.8 -3.8 1.9

CAR Region 1

38,308

34,568

90.2

38,989

33,901

86.9

39,689

34,391

86.7

-1.9

1.4

-3.7

-0.2

Ilocos Norte Ilocos Sur La Union Pangasinan Dagupan City Laoag City

11,929 16,509 18,212 58,362 3,809 2,677

11,870 13,430 17,094 51,141 3,832 3,030

99.5 81.4 93.9 87.6 100.6 113.2

12,029 16,657 18,505 59,191 3,832 2,703

10,236 12,298 15,452 50,499 3,605 2,891

85.1 73.8 83.5 85.3 94.1 106.9

12,130 16,807 18,803 60,031 3,855 2,730

4,455 5,423 7,154 23,780 1,781 1,370

36.7 32.3 38.0 39.6 46.2 50.2

-13.8 -8.4 -9.6 -1.3 -5.9 -4.6

-56.5 -55.9 -53.7 -52.9 -50.6 -52.6

-14.5 -9.3 -11.1 -2.6 -6.5 -5.6

-56.9 -56.2 -54.5 -53.6 -50.9 -53.0

CAR Abra Apayao Benguet Ifugao Kalinga Mt. Province Baguio City

Province/City

San Carlos City Region 1

1996 1997 1998 No. of % of No. of % of No. of % of % Change, Number % Change, Proportion Eligible immunized Eligible Eligible immunized Eligible Eligible immunized Eligible Population population Pop'n. Population population Pop'n. Population population Pop'n. 1996-1997 1997-1998 1996-1997 1997-1998 4,077 3,257 79.9 4,134 4,297 103.9 4,191 1,940 46.3 31.9 -54.9 30.0 -55.4 115,574

103,654

89.7

117,051

99,278

84.8

118,548

45,903

38.7

-4.2

Bataan Bulacan Nueva Ecija Pampanga Tarlac Zambales Angeles City Cabanatuan City Olongapo City Palayan City San Jose City

15,145 55,268 36,357 42,675 28,885 11,800 7,020 6,203 5,393 848 2,981

13,494 51,199 27,155 42,140 28,760 8,906 9,140 5,262 5,363 642 686

89.1 92.6 74.7 98.7 99.6 75.5 130.2 84.8 99.5 75.7 23.0

15,557 57,058 37,606 43,307 29,405 11,916 7,020 6,380 5,393 893 3,059

10,211 56,025 23,613 44,165 28,801 8,176 2,201 1,465 5,079 725 661

65.6 98.2 63.3 102.0 97.9 68.6 31.4 23.0 94.2 81.2 21.6

15,980 58,907

3,534 28,557

43,948 29,934 12,032 7,020 6,561 5,393 940 3,138

20,975 13,966 3,684 4,334 1,395 2,725 253 1,502

47.7 46.7 30.6 61.7 21.3 50.5 26.9 47.9

-24.3 9.4 -13.0 4.8 0.1 -8.2 -75.9 -72.2 -5.3 12.9 -3.6

Region 3

212,575

192,747

90.7

217,293

181,122

83.4

183,854

80,925

44.0

-6.0

4,911 38,901 46,883 44,861 6,082 10,545 18,607 15,890 41,628 41,611 7,439 6,520 2,785 5,443

7,804 35,756 36,099 40,907 4,847 8,806 17,550 12,590 34,751 36,539 6,840 6,543 1,660 1,375

158.9 91.9 77.0 91.2 79.7 83.5 94.3 79.2 83.5 87.8 91.9 100.3 59.6 25.3

5,036 39,757 49,917 46,351 6,168 10,914 18,963 16,473 42,473 43,975 7,541 6,689 2,790 5,551

4,512 36,950 44,975 43,554 5,132 10,239 18,140 12,703 34,883 41,910 6,249 6,341 3,001 5,599

89.6 92.9 90.1 94.0 83.2 93.8 95.7 77.1 82.1 95.3 82.9 94.8 107.5 100.9

5,164 40,632 53,146 47,890 6,255 11,296 19,325 17,078 43,335 46,472 7,643 6,861 2,796 5,662

4,285 36,935 47,220 44,908 4,546 9,307 18,972 9,026 11,234 36,441 4,428 6,532 2,958 5,673

83.0 90.9 88.8 93.8 72.7 82.4 98.2 52.9 25.9 78.4 57.9 95.2 105.8 100.2

-42.2 3.3 24.6 6.5 5.9 16.3 3.4 0.9 0.4 14.7 -8.6 -3.1 80.8 307.2

-53.8

-5.5

-54.4

Region 3 22.1 48.5

-65.1

-26.4 6.0 -15.3 3.3 -1.7 -9.1 -75.9 -72.9 -5.3 7.3 -6.1

-66.9

-8.0

Region 4 Aurora Batangas Cavite Laguna Marinduque Mindoro Occidental Mindoro Oriental Palawan Quezon Rizal Romblon Batangas City Cavite City Lipa City

-5.0 0.0 5.0 3.1 -11.4 -9.1 4.6

-13.0 -29.1 3.0 -1.4 1.3

-43.6 1.1 17.0 3.1 4.4 12.3 1.5 -2.7 -1.7 8.5 -9.8 -5.5 80.4 298.8

-7.4 -2.2 -1.4 -0.2 -12.6 -12.2 2.6

-17.7 -30.2 0.4 -1.6 -0.7

Province/City

Lucena City Puerto Princessa City San Pablo City Tagaytay City Trece Martires City

Eligible Population 5,500 4,144 5,647 919 645

1996 1997 1998 No. of % of No. of % of No. of % of % Change, Number % Change, Proportion immunized Eligible Eligible immunized Eligible Eligible immunized Eligible population Pop'n. Population population Pop'n. Population population Pop'n. 1996-1997 1997-1998 1996-1997 1997-1998 4,395 79.9 5,674 5,342 94.2 5,852 4,748 81.1 21.5 -11.1 17.9 -13.9 3,126 75.4 4,417 3,755 85.0 4,709 3,919 83.2 20.1 4.4 12.7 -2.1 4,975 88.1 5,784 5,509 95.2 5,924 5,141 86.8 10.7 -6.7 8.1 -8.8 225 24.5 956 942 98.5 996 1,057 106.2 318.7 12.2 302.0 7.8 169 26.2 678 865 127.6 712 951 133.5 411.8 9.9 387.0 4.6

Region 4 w/ complete records Region 5

308,962 251,444

264,957 217,616

85.8 86.55

320,105 261,159

290,601 243,015

90.8 93.05

331,748 271,335

258,281 238,021

77.9 87.7

9.7 11.7

Albay Camarines Norte Camarines Sur Catanduanes Masbate Sorsogon Iriga City Legaspi City Naga City

26,431 13,464 37,336 6,165 19,937 18,175 2,523 4,376 3,878

25,958 11,607 31,236 5,147 18,773 15,765 1,997 4,755 4,356

98.2 86.2 83.7 83.5 94.2 86.7 79.1 108.7 112.3

26,962 13,761 37,990 6,257 20,264 18,602 2,573 4,507 3,949

19,498 12,363 33,253 6,347 15,603 15,824 2,121 3,270 4,726

72.3 89.8 87.5 101.4 77.0 85.1 82.4 72.6 119.7

27,504 14,063 38,655 6,351 20,597 19,039 2,624 4,641 4,021

17,750 2,739 14,498 3,509 10,960 11,514 989 2,120 2,383

64.5 19.5 37.5 55.2 53.2 60.5 37.7 45.7 59.3

-24.9 6.5 6.5 23.3 -16.9 0.4 6.2 -31.2 8.5

132,287

119,594

90.4

134,865

113,005

83.8

137,495

66,462

48.3

-5.5

-7.3

12,492 13,099 15,364 42,896 41,486 3,844 12,297 4,026 3,814 10,184 1,692 3,656

16,170 11,818 13,655 37,178 40,353 3,742 12,422 4,114 5,444 9,538 1,533 2,934

129.4 90.2 88.9 86.7 97.3 97.4 101 102.2 142.7 93.7 90.6 80.2

12,671 13,248 15,557 43,347 42,042 3,894 12,528 4,082 3,850 10,333 1,692 3,753

8,092 11,071 12,489 32,929 59,199 3,227 12,450 3,729 3,712 9,803 1,428 3,190

63.9 83.6 80.3 76.0 140.8 82.9 99.4 91.4 96.4 94.9 84.4 85.0

12,852 13,399 15,753 43,802 42,606 3,945 12,764 4,139 3,887 10,485 1,692 3,853

4,340 5,044 5,304 12,222 16,444 1,407 8,617 1,875 3,010 3,769 1,002 1,633

33.8 37.6 33.7 27.9 38.6 35.7 67.5 45.3 77.4 35.9 59.2 42.4

-50.0 -6.3 -8.5 -11.4 46.7 -13.8 0.2 -9.4 -31.8 2.8 -6.8 8.7

-50.6 -7.3 -9.7 -12.3 44.7 -14.9 -1.6 -10.6 -32.4 1.3 -6.8 6.0

Region 5

-11.1 -2.1

-53.4

5.8 7.5

-26.4 4.2 4.5 21.4 -18.3 -1.8 4.2 -33.2 6.6

-14.2 -5.7

-54.25

Region 6 Aklan Antique Capiz Iloilo Negros Occ. Guimaras Bacolod City Bago City Cadiz City Iloilo City La Carlota City Roxas City

-62.9

-63.3

Province/City

San Carlos City Silay City Sagay City Region 6

1996 1997 1998 No. of % of No. of % of No. of % of % Change, Number % Change, Proportion Eligible immunized Eligible Eligible immunized Eligible Eligible immunized Eligible Population population Pop'n. Population population Pop'n. Population population Pop'n. 1996-1997 1997-1998 1996-1997 1997-1998 3,043 2,944 96.8 3,043 2,776 91.2 3,043 1,449 47.6 -5.7 -5.8 3,819 3,049 79.8 3,962 2,828 71.4 4,109 1,996 48.6 -7.2 -10.5 3,955 3,053 77.2 4,008 2,335 58.3 171,714

164,894

96.0

177,960

169,976

95.5

180,339

70,447

39.1

3.1

-0.5

28,080 51,687 25,319 2,213 1,923 1,265 20,175 2,437 2,855 5,384 5,928 2,065 3,652

24,664 36,685 22,462 1,510 1,589 904 19,299 2,655 2,649 5,618 6,688 1,843 972

87.8 71.0 88.7 68.2 82.7 71.5 95.7 109.0 92.8 104.4 112.8 89.3 26.6

28,330.0 52,726 25,811 2,213 1,945 1,290 20,486 2,476 2,932 5,561 6,014 2,131 3,661

23,081.0 44,116 22,236 1,471 1,651 1,067 16,967 2,698 2,713 6,220 6,523 1,722 3,679

81.5 83.7 86.2 66.5 84.9 82.7 82.8 109.0 92.5 111.9 108.5 80.8 100.5

28,582 53,786 26,311 2,213 1,967 1,316 20,801 2,516 3,012 5,744 6,102 2,199 3,669

22,704 45,280 21,193 1,467 1,289 1,025 17,501 2,684 3,127 6,133 6,855 1,939 3,383

79.4 84.2 80.5 66.3 65.5 77.9 84.1 106.7 103.8 106.8 112.3 88.2 92.2

-6.4 20.3 -1.0 -2.6 3.9 18.0 -12.1 1.6 2.4 10.7 -2.5 -6.6 278.5

-1.6 2.6 -4.7 -0.3 -21.9 -3.9 3.1 -0.5 15.3 -1.4 5.1 12.6 -8.0

-7.2 17.9 -2.8 -2.5 2.7 15.7 -13.5 0.0 -0.3 7.2 -3.8 -9.5 277.8

-2.6 0.6 -6.6 -0.3 -22.9 -5.8 1.6 -2.1 12.2 -4.6 3.5 9.2 -8.3

152,982

127,538

83.4

155,576

134,144

86.2

158,219

134,580

85.1

5.2

0.3

3.4

-1.3

42.9 19.5 36.8 42.1 45.5 41.2 32.4 50.1 30.9

-3.9 -5.4 -27.5 5.6 -10.1 -5.1 -29.7 0.9 56.6

Region 7 Bohol Cebu Negros Or. Siquijor Bais City Canlaon City Cebu City Danao City Dumaguete City Lapu-Lapu City Mandawe City Tagbilaran City Toledo City Region 7 Region 8 Biliran Leyte Del Norte Leyte Del Sur Eastern Samar Northern Samar Western Samar Calbayog City Ormoc City Tacloban City

4,052 36,679 9,527 11,065 14,063 14,064 3,959 4,407 5,212

3,869 32,602 11,332 10,209 10,917 13,195 4,562 4,515 3,326

95.5 88.9 118.9 92.3 77.6 93.8 115.2 102.4 63.8

4,139 37,372 9,527 11,265 14,515 14,329 4,044 4,496 5,411

3,717 30,838 8,213 10,782 9,810 12,516 3,209 4,554 5,208

89.8 82.5 86.2 95.7 67.6 87.3 79.3 101.3 96.2

4,228 38,078 9,527 11,467 14,981 14,598 4,131 4,587 5,618

1,813 7,415 3,506 4,826 6,823 6,009 1,339 2,299 1,737

-6.0 -7.2 -27.5 3.7 -12.9 -6.9 -31.2 -1.1 50.8

Province/City

Region 8

1996 1997 1998 No. of % of No. of % of No. of % of % Change, Number % Change, Proportion Eligible immunized Eligible Eligible immunized Eligible Eligible immunized Eligible Population population Pop'n. Population population Pop'n. Population population Pop'n. 1996-1997 1997-1998 1996-1997 1997-1998 103,028 94,527 91.7 105,097 88,847 84.5 107,215 35,767 33.4 -6.0 -7.9

Region 10 Bukidnon Camiguin Misamis Occidental Misamis Oriental Cagayan De Oro City Gingoog City Oroquieta Ozamis City Tangub City

28,790 2,063 7,763 15,319 13,420 2,655 1,701 3,121 1,398

28,116 1,941 5,173 14,247 13,645 2,684 1,767 1,562 1,121

97.7 94.1 66.6 93.0 101.7 101.1 103.9 50.0 80.2

29,381 2,086 7,878 15,643 14,016 2,684 1,722 3,185 1,417

26,869 1,735 5,987 14,370 12,063 2,387 1,528 3,108 1,005

91.5 83.2 76.0 91.9 86.1 88.9 88.8 97.6 70.9

29,983 2,108 7,995 15,975 14,638 2,714 1,743 3,250 1,435

27,520 1,914 1,453 14,565 13,049 1,988 1,556 3,748 1,225

91.8 90.8 18.2 91.2 89.1 73.3 89.3 115.3 85.4

-4.4 -10.6 15.7 0.9 -11.6 -11.1 -13.5 99.0 -10.3

2.4 10.3

Region 10 w/ complete records

76,230

70,256

92.2

78,011 66,949

69,052 59,957

88.5 89.6

79,840 68,596

67,018 61,817

83.9 90.1

-1.7

19,134 12,512 36,558 11,558 20,572 31,178 10,317

17,893 11,519 29,739 9,476 18,477 24,764 8,197

93.5 92.1 81.3 82.0 89.8 79.4 79.5

19,647 12,621 37,392 12,134 20,835 32,182 10,850

16,162 11,326 32,179 9,898 18,135 29,858 9,583

82.3 89.7 86.1 81.6 87.0 92.8 88.3

20,173 12,731 38,244 12,738 21,102 33,218 11,408

8,194 4,285 6,656 4,815 3,726 14,398 4,782

40.6 33.7 17.4 37.8 17.7 43.3 41.9

-9.7 -1.7 8.2 4.5 -1.9 20.6 16.9

-12.0 -2.6 5.9 -0.5 -3.1 16.9 11.1

141,830

120,065

84.7

145,661

127,141

87.3

149,615

46,857

31.3

5.9

3.1

13,546 26,475 16,205 4,524 8,482

9,527 23,758 12,815 4,666 7,150

70.3 89.7 79.1 103.1 84.3

13,877 27,084 16,762 4,648 8,784

9,953 25,100 13,203 5,237 7,625

71.7 92.7 78.8 112.7 86.8

14,215 27,707 17,339 4,775 9,096

33.7 40.4 56.3 39.0 38.7

4.5 5.6 3.0 12.2 6.6

2.0 3.3 -0.4 9.3 3.0

1.4 8.2 -16.7 1.8 21.9 -2.9 3.1

-6.3 -11.6 14.1 -1.2 -15.3 -12.1 -14.5 95.2 -11.6 -4.0

0.3 9.1 -0.8 3.5 -17.5 0.6 20.5 -5.2 0.6

Region 11 South Cotabato Davao Oriental Davao Del Norte Sarangani Davao Del Sur Davao City General Santos City Region 11 Region 12 Lanao Del Norte North Cotabato Sultan Kudarat Cotabato City Iligan City

4,784 11,192 9,762 1,861 3,516

-53.9

-55.4

Province/City

Marawi City

1996 1997 1998 No. of % of No. of % of No. of % of % Change, Number % Change, Proportion Eligible immunized Eligible Eligible immunized Eligible Eligible immunized Eligible Population population Pop'n. Population population Pop'n. Population population Pop'n. 1996-1997 1997-1998 1996-1997 1997-1998 3,575 1,295 36.2 3,725 2,474 66.4 3,881 1,314 33.9 91.0 -46.9 83.4 -48.9

Region 12 w/ complete records Note: # -no data * - 1st quarter report only **- 2nd quarter report only ***-3rd quarter report only

72,807 12,057

59,211 8,445

81.3 70.04

74,880 12,509

Source: DOH, Field Health Services and Information Systems (FHSIS), Manila.

63,592 10,099

84.9 80.7

77,014 12,977

32,429 4,830

42.1 37.2

7.4 19.6

-49.0 -52.2

4.4 15.3

-50.4 -53.9

TABLE V.26 NUTRITION PROGRAM PERFORMANCE, 1996 - 1998

MODERATELY UNDERWEIGHT Province/City

Eligible Population

No.

%

1996 SEVERELY UNDERWEIGHT No.

%

MODERATELY & SEVERELY UNDERWEIGHT No. %

MODERATELY UNDERWEIGHT Eligible Population

No.

1997 SEVERELY UNDERWEIGHT

%

MODERATELY & SEVERELY UNDERWEIGHT No. %

MODERATELY UNDERWEIGHT Eligible Population

No.

%

% CHANGE IN NUMBER OF % CHANGE IN PROPORTION O MODERATELY & MODERATELY & SEVERELY MODERATELY & SEVERELY SEVERELY UNDERWEIGHT UNDERWEIGHT UNDERWEIGHT No. % 1996-1997 1997-1998 1996-1997

1998 SEVERELY UNDERWEIGHT No.

%

NCR 1s Dist. Mun. Manila 2nd Dist. Mun. Quezon City 3rd Dist. Mun. Caloocan City 4th Dist Mun. Pasay City

129,054 203,133 160,658 250,816 110,919 131,866 155,732 50,828

5,878 9,406 4,897 15,719 2,628 4,426 5,995 2,551

4.6 4.6 3.0 6.3 2.4 3.4 3.8 5.0

740 639 857 1,707 253 754 729 273

0.6 0.3 0.5 0.7 0.2 0.6 0.5 0.5

6,618 10,045 5,754 17,426 2,881 5,180

5.1 4.9 3.6 6.9 2.6 3.9

4,119 5,022 4,079 8,069 1,535 3,774 2,300 554

3.1 2.5 2.4 3.1 1.4 2.7 1.4 1.1

869 589 795 632 175 208 258 59

0.6 0.3 0.5 0.2 0.2 0.1 0.2 0.1

4,988 5,611 4,874 8,701 1,710 3,982

3.7 2.7 2.9 3.4 1.5 2.9

5.6

134,674 204,392 167,309 259,193 112,656 139,303 165,093 51,824

613

1.2

140,541 205,659 174,293 267,850 114,429 147,159 175,033 52,839

2,824

NCR

1,193,004

51,500

4.3

5,952

0.5

Abra Apayao Benguet Ifugao Kalinga Mt. Province Baguio City

24,173 10,425 38,548 18,304 19,225 16,300 28,812

9,351 1,309 3,683 2,007 1,946 2,440 1,225

38.7 12.6 9.6 11.0 10.1 15.0 4.3

2,407 85 328 164 281 213 12

CAR

155,786

21,961

14.1

48,510 67,136 74,061 237,338 15,490 10,885 16,580

3,385 14,390 12,253 42,778 5763 3,182 2,081

470,001

# # # # # # # #

57,452

4.8

1,234,443

29,452

2.4

3,585

0.3

33,037

2.7

1,277,804

10.0 0.8 0.9 0.9 1.5 1.3 0.04

11,758 1,394 4,011 2,171 2,227 2,653 1,237

48.6 13.4 10.4 11.9 11.6 16.3 4.3

24,441 10,648 38,810 18,357 19,654 16,655 29,990

6,098 2,193 3,043 1,392 1,987 2,014 199

24.9 20.6 7.8 7.6 10.1 12.1 0.7

1,577 141 330 112 325 136 16

6.5 1.3 0.9 0.6 1.7 0.8 0.1

7,675 2,334 3,373 1,504 2,312 2,150 215

31.4 21.9 8.7 8.2 11.8 12.9 0.7

24,713 10,876 39,074 18,410 20,092 17,018 31,217

7,617 3,271 2,254 1,628 2,004 1,022 589

30.8 30.1 5.8 8.8 10.0 6.0 1.9

1,832 7.4 616 5.7 193 0.5 141 0.8 175 0.9 78 0.5 15 0.05

3,490

2.2

25,451

16.3

158,556

16,926

10.7

2,637

1.7

19,563

12.3

161,400

18,385

11.4

3,050

7.0 21.4 16.5 18.0 37.2 29.2 12.6

1,909 2,112 3,466 10,694 4,695 153 342

3.9 3.1 4.7 4.5 30.3 1.4 2.1

5,294 16,502 15,719 53,472 10,458 3,335 2,423

10.9 24.6 21.2 22.5 67.5 30.6 14.6

48,918 67,740 75,254 240,709 15,583 10,994 16,811

6,795 10,846 9,378 35,647 2,582 24 1,565

13.9 16.0 12.5 14.8 16.6 0.2 9.3

1,031 1,171 1,559 4,593 444 0 269

2.1 1.7 2.1 1.9 2.8 1.6

7,826 12,017 10,937 40,240 3,026 24 1,834

16.0 17.7 14.5 16.7 19.4 0.2 10.9

49,329 68,350 76,465 244,127 15,677 11,104 17,044

2,292 5,486 5,036 14,648 2,087 0 2,181

4.6 8.0 6.6 6.0 13.3 12.8

83,832

17.8

23,371

5.0

107,203

22.8

476,008

66,837

14.0

9,067

1.9

75,904

15.9

482,095

31,730

61,589 224,755 147,853 173,545 117,466 47,986 28,549 25,225 21,930 12,124

5,661 21,164 20,360 18,205 12,101 20,604 1,045 2,433 3,366 419

9.2 9.4 13.8 10.5 10.3 42.9 3.7 9.6 15.3 3.5

807 2,708 5,170 2,403 2,746 1,919 103 554 827 41

1.3 1.2 3.5 1.4 2.3 4.0 0.4 2.2 3.8 0.3

6,468 23,872 25,530 20,608 14,847 22,523 1,148 2,987 4,193

10.5 10.6 17.3 11.9 12.6 46.9 4.0 11.8 19.1

460

3.8

63,264 232,037 151,712 176,114 119,580 48,456 28,549 25,944 21,930 3,632 12,439

5,427 12,907 16,344 10,774 9,046 9,045 487 534 2,605 369 587

8.6 5.6 10.8 6.1 7.6 18.7 1.7 2.1 11.9 10.2 4.7

753 3,175 2,738 1,224 2,671 787 31 145 781 65 34

1.2 1.4 1.8 0.7 2.2 1.6 0.1 0.6 3.6 1.8 0.3

6,180 16,082 19,082 11,998 11,717 9,832 518 679 3,386 434 621

9.8 6.9 12.6 6.8 9.8 20.3 1.8 2.6 15.4 11.9 5.0

64,985 239,555 178,720 121,733 48,931 28,549 26,683 21,930 3,824 12,763

1,626 6,350 3,520 5,191 3,214 995 387 407 255 1,894

861,023

105,358

12.2

2

122,636

14.2

883,658

68,125

7.7

12,404

1.4

80,529

9.1

-24.6 -44.1 -15.3 -50.1 -40.6 -23.1

-27.8 -44.5 -18.7 -51.7 -41.6 -27.2

-78.3

-78.7

-42.5

-44.4

CAR 9,449 3,887 2,447 1,769 2,179 1,100 604

38.2 35.7 6.3 9.6 10.8 6.5 1.9

-34.7 67.4 -15.9 -30.7 3.8 -19.0 -82.6

23.1 66.5 -27.5 17.6 -5.8 -48.8 180.9

-35.4 63.9 -16.5 -30.9 1.6 -20.7 -83.3

1.9

21,435

13.3

-23.1

9.6

-24.5

279 993 725 2,856 389 0 362

0.6 1.5 0.9 1.2 2.5 2.1

2,571 6,479 5,761 17,504 2,476 0 2,543

5.2 9.5 7.5 7.2 15.8 0.0 14.9

47.8 -27.2 -30.4 -24.7 -71.1 -99.3 -24.3

46.6 -27.8 -31.5 -25.8 -71.2 -99.3 -25.3

6.6

5,604

1.2

37,334

7.7

-29.2

-30.1

2.5 2.7 2.0 4.3 6.6 3.5 1.5 1.9 6.7 14.8

217 690 501 895 111 226 159 31 113

0.3 0.3 0.3 0.7 0.4 0.8 0.7 0.8 0.9

1,843 7,040

2.8 2.9

4,021 6,086

2.2 5.0

1,106 613 566 286 2,007

3.9 2.3 2.6 7.5 15.7

-4.5 -32.6 -25.3 -41.8 -21.1 -56.3 -54.9 -77.3 -19.2

0.4

26,782

3.6

Region 1 Ilocos Norte Ilocos Sur La Union Pangasinan Dagupan City Laoag City San Carlos City Region 1 Region 3 Bataan Bulacan Nueva Ecija Pampanga Tarlac Zambales Angeles City Cabanatuan City Olongapo City Palayan City San Jose City Region 3 Region 4

17,278

747,674

23,839

3.2

2,943

-70.2 -56.2 -66.5 -48.1

35.0

113.5 -9.7 -83.3 -34.1 223.2

-34.3

-66.7

-7.0 -34.7 -27.2 -42.6 -22.5 -56.8 -54.9 -77.9 -19.2 31.6 -36.0

1996 SEVERELY UNDERWEIGHT

MODERATELY UNDERWEIGHT

No. 5,943 16,504 7,987 24,423 780 3,073 9,272 14,309 20,305 15,976 244 831 2,562 1,060 5,360 836 670

% 29.8 10.4 4.2 13.4 3.2 7.2 12.3 22.1 12.0 9.4 0.8 3.1 22.6 4.8 24.0 5.0 2.9

14.3

375

14.3

MODERATELY & SEVERELY UNDERWEIGHT Eligible No. % Population 11,886 59.5 20,480 33,008 20.9 161,679 15,974 8.4 202,995 48,846 26.8 188,493 1,560 6.3 25,082 6,146 14.3 44,383 18,544 24.5 771,155 28,618 44.3 66,990 40,610 24.0 172,724 31,952 18.9 178,830 4,540 15.0 30,665 1,662 6.3 27,200 5,124 45.2 11,347 2,120 9.6 22,575 10,720 47.9 23,073 1,672 9.9 17,964 1,340 5.8 23,521 3,889 750 28.6 2,756

134,562

10.7

130,510

10.4

265,072

107,484 54,755 151,835 25,071 81,078 73,912 10,262 17,797

34,866 19,749 40,862 7,882 6,772 24,159 5,271 175

32.4 36.1 26.9 31.4 8.4 32.7 51.4 1.0

10,241 4,696 14,081 1,743 10,356 4,179 520 172

9.5 8.6 9.3 7.0 12.8 5.7 5.1 1.0

117,725 59,451 165,916 26,814 91,434 78,091 10,782 17,969

109.5 108.6 109.3 107.0 112.8 105.7 105.1 101.0

109,645 55,960 154,492 25,447 82,408 75,649 10,465 18,328

28,779 10,643 47,349 10,070 10,660 22,557 3,236 175

522,195 504,398

137,983 137,808

26.8 27.3

45,988 45,816

8.8 9.1

568,183 550,214

108.8 109.1

532,393 514,065

50,802 53,269 62,479 174,445 168,711 15,631 50,009 16,371 15,511 41,414 6,883 14,869 12,374 15,532

11,092 6,124 9,090 76,273 9,024 2,576 3,846 1,520 6,758 5,753 1,455 1,252 2,312 908

21.8 11.5 14.5 43.7 5.3 16.5 7.7 9.3 43.6 13.9 21.1 8.4 18.7 5.8

1,346 373 1,931 8,189 2,681 244 417 70 495 367 43 154 178 54

2.6 0.7 3.1 4.7 1.6 1.6 0.8 0.4 3.2 0.9 0.6 1.0 1.4 0.3

12,438 6,497 11,021 84,462 11,705 2,820 4,263 1,590 7,253 6,120 1,498 1,406 2,490 962

24.5 12.2 17.6 48.4 6.9 18.0 8.5 9.7 46.8 14.8 21.8 9.5 20.1 6.2

16,542

2.4

154,525

22.1

Province/City

Eligible Population Aurora 19,970 Batangas 158,198 Cavite 190,659 Laguna 182,436 Marinduque 24,733 Mindoro Occidental 42,882 Mindoro Oriental 75,669 Palawan 64,618 Quezon 169,287 Rizal 169,219 Romblon 30,254 Batangas City 26,516 Cavite City 11,325 Lipa City 22,135 Lucena City 22,369 Puerto Princessa City 16,852 San Pablo City 22,963 Tagaytay City Trece Martires City 2,622

No. 5,943 16,504 7,987 24,423 780 3,073 9,272 14,309 20,305 15,976 4,296 831 2,562 1,060 5,360 836 670

% 29.8 10.4 4.2 13.4 3.2 7.2 12.3 22.1 12.0 9.4 14.2 3.1 22.6 4.8 24.0 5.0 2.9

375

1,252,707

Albay Camarines Norte Camarines Sur Catanduanes Masbate Sorsogon Iriga City Legaspi City Naga City Region 5 w/ complete records

Region 4

#

#

21.2 1,301,761

MODERATELY UNDERWEIGHT

116 100,613

No. 1,803 16,313 10,675 9,621 1,255 1,782 6,399 9,497 16,694 17,581 4,067 605 1,049 1,011 1,488 288 369

1997 SEVERELY UNDERWEIGHT

266 2,939 2,619 1,191 80 164 987 926 3,889 6,130 292 91 89 150 236 4 24

1.3 1.8 1.3 0.6 0.3 0.4 1.3 1.4 2.3 3.4 1.0 0.3 0.8 0.7 1.0 0.02 0.1

4.2

7

0.3

MODERATELY & SEVERELY UNDERWEIGHT Eligible No. % Population 2,069 10.1 21,002 19,252 11.9 165,236 13,294 6.5 216,129 10,812 5.7 194,751 1,335 5.3 25,435 1,946 4.4 45,936 7,386 1.0 78,588 10,423 15.6 69,449 20,583 11.9 176,230 23,711 13.3 188,988 4,359 14.2 31,082 696 2.6 27,902 1,138 10.0 11,370 1,161 5.1 23,025 1,724 7.5 23,800 292 1.6 19,150 393 1.7 24,093 4,049 123 4.5 2,897

7.7

20,084

1.5

120,697

% 8.8 10.1 5.3 5.1 5.0 4.0 8.3 14.2 9.7 9.8 13.3 2.2 9.2 4.5 6.4 1.6 1.6 #

#

9.3 1,349,109

MODERATELY UNDERWEIGHT

59,923

4.4

No. 948 13,364 5,507 7,444 1,233 2,527 4,272 6,462 49 10,982 4,571 734 737 425 0 123 422 123

1998 SEVERELY UNDERWEIGHT

% 4.5 8.1 2.5 3.8 4.8 5.5 5.4 9.3 *** 0.03 *** 5.8 14.7 2.6 6.5 1.8 0.6 1.8 # 4.2

% CHANGE IN NUMBER OF % CHANGE IN PROPORTION O MODERATELY & MODERATELY & SEVERELY MODERATELY & SEVERELY SEVERELY UNDERWEIGHT UNDERWEIGHT UNDERWEIGHT No. % 1996-1997 1997-1998 1996-1997 1,111 5.3 -82.6 -46.3 -83.0 16,065 9.7 -41.7 -16.6 -42.9 6,402 3.0 -16.8 -51.8 -21.8 8,698 4.5 -77.9 -19.6 -78.6 1,325 5.2 -14.4 -0.7 -15.6 2,897 6.3 -68.3 48.9 -69.4 6,070 7.7 -60.2 -17.8 -96.1 7,082 10.2 -63.6 -32.1 -64.9 85 0.0 -49.3 -99.6 -50.3 14,342 7.6 -25.8 -39.5 -29.8 4,865 15.7 -4.0 11.6 -5.3 846 3.0 -58.1 21.6 -59.2 815 7.2 -77.8 -28.4 -77.8 479 2.1 -45.2 -58.7 -46.3 0 0.0 -83.9 -100.0 -84.4 638 3.3 -82.5 118.5 -83.6 460 1.9 -70.7 17.0 -71.4

No. % 163 0.8 2,701 1.6 895 0.4 1,254 0.6 92 0.4 370 0.8 1,798 2.3 620 0.9 36 0.02 3,360 1.8 294 0.9 112 0.4 78 0.7 54 0.2 0 515 2.7 38 0.2 # 4

0.1

127

4.4

-83.6

3.3

-84.4

12,384

0.9

72,307

5.4

-54.5

-40.1

-56.2

3,162 259 4,090 1,358 2,924 823 74 37

2.8 0.5 2.6 5.3 3.5 1.1 0.7 0.2

21,894 2,562 21,177 9,281 13,807 8,009 1,352 90

19.6 4.5 13.5 35.9 16.5 10.3 12.7 0.5

17.6 12.0 21.7 32.5 1.8 25.8 27.1 3.0

15.3 9.6 19.6 30.5 0.1 22.9 24.6 0.0

Region 5 26.2 19.0 30.6 39.6 12.9 29.8 30.9 1 * #

109,645 55,960 154,492 25,447 82,408 75,649 10,465 18,328

133,469 133,294

25.1 25.9

532,393 514,065

51,528 53,877 63,267 176,277 170,972 15,836 50,949 16,600 15,658 42,023 6,883 15,264 12,374 16,084 16,110

4,968 5,690 6,835 45,017 17,084 881 10,803 1,646 2,109 2,078 704 707 465 1,052 3,114

9.6 10.6 10.8 25.5 10.0 5.6 21.2 9.9 13.5 4.9 10.2 4.6 3.8 6.5 19.4

723,702

103,153

14.3

6.5 3.9 0.3 10.2 3.7 3.9 2.3 0.9 * #

138,424 66,603 201,841 35,517 93,068 98,206 13,701 18,503

126.2 119.0 130.6 139.6 112.9 129.8 130.9 101.0

111,848 57,191 157,196 25,829 83,759 77,427 10,672 18,874

18,732 2,303 17,087 7,923 10,883 7,186 1,278 53

16.7 4.0 10.9 30.7 13.0 9.3 12.0 0.3

** * ** ** ** ** ** ** #

** * ** ** ** ** ** ** #

3.5 100.0

665,862 647,359

125.1 125.9

542,796

65,445

12.1

12,727

2.3

78,172

14.4

17.2 17.7

14.9 15.4

402 355 863 5,315 1,820 343 515 111 175 212 7 85 43 35 480

0.8 0.7 1.4 3.0 1.1 2.2 1.0 0.7 1.1 0.5 0.1 0.6 0.3 3.0 0.2

5,370 6,045 7,698 50,332 18,904 1,224 11,318 1,757 2,284 2,290 711 792 508 1,087 3,594

10.4 11.2 12.2 28.6 11.1 7.7 22.2 10.6 14.6 5.4 10.3 5.2 4.1 6.8 22.3

52,265 54,491 64,064 178,128 173,263 16,044 51,907 16,833 15,807 42,640 6,883 15,670 12,374 16,709 16,300

3,998 10,190 1,465 14,550 3,584 1,160 3,588 867 897 4,828 92 566 937 3,032

7.6 18.7 2.3 8.2 2.1 7.2 6.9 5.2 5.7 11.3 1.3 3.6

160 482 203 1,968 280 70 343 45 47 469 1 55 72 230

0.3 0.9 0.3 1.1 0.2 0.4 0.7 0.3 0.3 1.1 0.01 0.4

** ** ** ** ** ** *** ** *** ** *** ** ** 0.4 *** 1.4 ***

4,158 10,672 1,668 16,518 3,864 1,230 3,931 912 944 5,297 93 621

8.0 19.6 2.6 9.3 2.2 7.7 7.6 5.4 6.0 12.4 1.4 4.0

1,009 3,262

6.0 20.0

-56.8 -7.0 -30.2 -40.4 61.5 -56.6 165.5 10.5 -68.5 -62.6 -52.5 -43.7 -79.6 13.0

-57.4 -8.0 -31.0 -41.0 59.4 -57.2 160.6 9.0 -68.8 -63.1 -52.5 -45.1 -79.6 9.1

10,761

1.5

113,914

15.7

733,378

49,754

6.8

4,425

0.6

54,179

7.4

-26.3

-28.9

Region 6 Aklan Antique Capiz Iloilo Negros Occ. Guimaras Bacolod City Bago City Cadiz City Iloilo City La Carlota City Roxas City San Carlos City Silay City Sagay City Region 6

# 698,302

137,983

19.8

** ** ** ** ** ** ** ** ** ** *** ** ** 5.6 *** 18.6 ***

1996 SEVERELY UNDERWEIGHT

MODERATELY UNDERWEIGHT Province/City

Eligible Population

No.

%

No.

%

MODERATELY & SEVERELY UNDERWEIGHT No. %

MODERATELY UNDERWEIGHT Eligible Population

No.

1997 SEVERELY UNDERWEIGHT

%

MODERATELY & SEVERELY UNDERWEIGHT No. %

1998 SEVERELY UNDERWEIGHT

MODERATELY UNDERWEIGHT Eligible Population

No.

%

No.

%

% CHANGE IN NUMBER OF % CHANGE IN PROPORTION O MODERATELY & MODERATELY & SEVERELY MODERATELY & SEVERELY SEVERELY UNDERWEIGHT UNDERWEIGHT UNDERWEIGHT No. % 1996-1997 1997-1998 1996-1997

Region 7 Bohol Cebu Negros Or. Siquijor Bais City Canlaon City Cebu City Danao City Dumaguete City Lapu-Lapu City Mandawe City Tagbilaran City Toledo City Region 7

114,194 210,194 102,966 8,998 7,818 5,144 82,045 9,910 11,609 21,894

9,485 12,436 11,657 858 1,005 431 34,927 570 405 1,222

8.3 5.9 11.3 9.5 12.9 8.4 42.6 5.8 3.5 5.6

1,182 3,304 2,072 74 208 63 1,970 78 15 994

1.0 1.6 2.0 0.8 2.7 1.2 2.4 0.8 0.1 4.5

10,667 15,740 13,729 932 1,213 494 36,897 648 420 2,216

9.3 7.5 13.3 10.4 15.5 9.6 45.0 6.5 3.6 10.1

8,396 14,853

169 199

598,021

73,364

8,262 8,432 13,605 794 511 243 11,448 1,740 258 932 1,642 321 920

7.2 3.9 13.0 8.8 6.5 4.6 13.7 17.3 2.2 4.1 6.7 3.7 6.2

924 2,373 1,926 24 61 31 526 375 15 111 48

0.8 1.1 1.8 0.3 0.8 0.6 0.6 3.7 0.1 0.5 0.2

2.0 1.5

115,210 214,419 104,963 8,998 7,908 5,247 83,308 10,070 11,925 22,614 24,458 8,664 14,887

2.0 1.3

27

0.2

169 226

83

12.3

9,987

1.7

83,351

13.9

632,674

49,108

7.8

6,497

#

8.0 5.0 14.8 9.1 7.2 5.2 14.4 21.0 2.3 4.6 6.9 3.7 6.7

116,235 218,729 107,000 8,998 7,999 5,353 84,591 10,233 12,249 23,358 24,815 8,942 14,922

4,339 10,812 20,509 682 2,381 1,755 4,953 1,799 725 920 1,095 123 897

3.7 4.9 19.2 7.6 29.8 32.8 5.9 17.6 5.9 3.9 4.4 1.4 6.0

428 1,459 2,593 45 364 231 502 182 43 131 68 2 139

0.4 0.7 2.4 0.5 4.6 4.3 0.6 1.8 0.4 0.6 0.3 0.0 0.9

4,767 12,271 23,102 727 2,745 1,986 5,455 1,981 768 1,051 1,163 125 1,036

4.1 5.6 21.6 8.1 34.3 37.1 6.4 19.4 6.3 4.5 4.7 1.4 6.9

-13.9 -31.4 13.1 -12.2 -52.8 -44.5 -67.5 226.4 -35.0 -52.9

0.6

9,186 10,805 15,531 818 572 274 11,974 2,115 273 1,043 1,690 321 1,003

-14.6 -32.7 11.0 -12.2 -53.4 -45.6 -68.0 221.2 -36.7 -54.4

89.9 343.8

-48.1 13.6 48.7 -11.1 379.9 624.8 -54.4 -6.3 181.3 0.8 -31.2 -61.1 3.3

1.0

55,605

8.8

643,425

50,990

7.9

6,187

1.0

57,177

8.9

-33.3

2.8

-36.9

3,438 7,704 3,820 5,857 10,568 13,753 1,701 3,232 3,225

20.0 5.0 9.9 12.6 17.3 23.2 10.1 17.3 14.1

135.8 -21.5 -26.1 -6.6 -55.6 -15.4 19.7 -25.1 -84.4

130.8 -23.0 -26.1 -8.2 -57.0 -17.0 17.2 -26.6 -84.9 -25.2

84.1 342.8

Region 8 Biliran Leyte Del Norte Leyte Del Sur Eastern Samar Northern Samar Western Samar Calbayog City Ormoc City Tacloban City

16,476 149,159 38,743 44,999 57,191 57,195 16,102 17,923 21,194

3,109 37,061 12,110 11,339 18,351 19,108 3,181 4,640 7,975

18.9 24.8 31.3 25.2 32.1 33.4 19.8 17923.0 37.6

450 8,489 2,611 4,784 3,431 5,949 519 1,628 1,397

2.7 5.7 6.7 10.6 6.0 10.4 3.2 9.1 6.6

3,559 45,550 14,721 16,123 21,782 25,057 3,700 6,268 9,372

21.6 30.5 38.0 35.8 38.1 43.8 23.0 35.0 44.2

16,831 151,978 38,743 45,809 59,026 58,270 16,446 18,285 22,005

7,923 29,258 9,823 11,843 6,335 16,927 3,553 4,002 1,140

47.1 19.3 25.4 25.9 10.7 29.0 21.6 21.9 5.2

469 6,488 1,056 3,220 3,333 4,265 875 694 325

2.8 4.3 2.7 7.0 5.6 7.3 5.3 3.8 1.5

8,392 35,746 10,879 15,063 9,668 21,192 4,428 4,696 1,465

49.9 23.5 28.1 32.9 16.4 36.4 26.9 25.7 6.7

17,192 154,851 38,743 46,634 60,921 59,365 16,798 18,655 22,848

3,214 6,548 3,472 4,543 8,942 11,712 1,445 2,935 2,703

18.7 4.2 9.0 9.7 14.7 19.7 8.6 15.7 11.8

418,981

116,874

27.9

29,258

7.0

146,132

34.9

427,394

90,804

21.2

20,725

4.8

111,529

26.1

436,007

45,514

Bukidnon Camiguin Misamis Occidental Misamis Oriental Cagayan De Oro City Gingoog City Oroquieta Ozamis City Tangub City

117,081 8,390 34,571 62,296 54,574 10,796 6,917 12,692 -

13,552 2,883 7,053 8,928 2,902 2,685 630 298 -

11.6 34.4 22.3 14.3 5.3 24.9 9.1 2.3 -

1,409 311 1,440 974 294 640 71 18 -

1.2 3.7 4.6 1.6 0.5 5.9 1.0 0.1 -

14,961 3,194 8,493 9,902 3,196 3,325 701 316

12.8 38.1 24.6 15.9 5.9 30.8 10.1 2.5

119,481 8,481 32,038 63,617 56,998 10,915 7,001 12,952 5,760

12,679 1,406 6,252 6,263 5,914 2,234 331 416 737

10.6 16.6 19.5 9.8 10.4 20.5 4.7 3.2 12.8

976 58 1,143 675 243 417 433 33 124

0.8 0.7 3.6 1.1 0.4 3.8 6.2 0.3 2.2

13,655 1,464 7,395 6,938 6,157 2,651 764 449 861

11.4 17.3 23.1 10.9 10.8 24.3 10.9 3.5 14.9

121,931 8,573 32,513 64,965 59,528 11,035 7,087 13,218 5,836

Region 10 w/ complete records

304,318

38,931

12.8

5,157

1.7

44,088

14.5

317,244 285,205

36,232 29,980

11.4 10.5

4,102 2,959

1.3 1.0

40,334 32,939

12.7 11.5

Region 11 South Cotabato Davao Oriental Davao Del Norte Davao Del Sur Davao City General Santos City

77,812 50,882 148,670 83,660 126,790 41,956

5,539 3,444 8,690 5,770

7.1 6.8 5.8 6.9

593 421 856 884

0.8 0.8 0.6 1.1

2,606

6.2

342

0.8

6,132 3,865 9,546 6,654 9,615 2,948

7.9 7.6 6.4 8.0 7.6 7.0

79,897 51,325 152,060 84,731 130,872 44,124

106 1,539 4,844 99 8,417 876

0.1 3.0 3.2 0.1 6.4 2.0

24 186 474 12 1,213 174

0.03 0.4 0.3 0.01 0.9 0.4

130 1,725 5,318 111 9,630 1,050

Region 11

576,774

37,295

6.5

4,539

0.8

41,834

7.3

592,354

17,036

2.9

2,171

0.4

19,207

Region 8

** ** ** ** ** ** ** ** **

224 1,156 348 1,314 1,626 2,041 256 297 522

1.3 0.7 0.9 2.8 2.7 3.4 1.5 1.6 2.3

** ** ** ** ** ** ** ** **

10.4

7,784

1.8

53,298

12.2

-23.7

10,621 724 1,954 3,889 1,712 1,753 436 2,370 223

8.7 8.4 6.0 6.0 2.9 15.9 6.2 17.9 3.8

896 74 472 399 111 433 41 189 14

0.7 0.9 1.5 * 0.6 0.2 3.9 0.6 1.4 0.2

11,517 798 2,426 4,288 1,823 2,186 477 2,559 237

9.4 9.3 7.5 6.6 3.1 19.8 6.7 19.4 4.1

-8.7 -54.2 -12.9 -29.9 92.6 -20.3 9.0 42.1

324,684 292,173

23,682 21,728

7.3 7.4

2,629 2,157

0.8 0.7

26,311 23,885

8.1 8.2

-8.5

0.2 3.4 3.5 0.1 7.4 2.4

82,038 51,772 155,527 51,803 135,086 46,392

285 1,124 1,080 590 2,783 336

0.3 2.2 0.7 1.1 2.1 0.7

86 146 20 51 484 89

0.1 0.3 0.0 0.1 0.4 0.2

371 1,270 1,100 641 3,267 425

0.5 2.5 0.7 1.2 2.4 0.9

-97.9 -55.4 -44.3 -98.3 0.2 -64.4

-97.9 -55.8 -45.5 -98.4 -3.0 -66.1

3.2

608,433

6,256

1.0

888

0.1

7,144

1.2

-54.1

-55.3

Region 10

Region 12

-15.7 -45.5 -38.2 -70.4 -17.5 -37.6 469.9 -72.5 -34.8 -27.5

-10.6 -54.7 -6.0 -31.4 84.5 -21.1 7.7 39.2

-12.2

MODERATELY UNDERWEIGHT Province/City Lanao Del Norte North Cotabato Sultan Kudarat Cotabato City Iligan City Marawi City Region 12

1996 SEVERELY UNDERWEIGHT

Eligible Population 55,088 107,666 65,898 18,398 34,492 14,540

No. 9,148 18,268 10,054 1,978 2,296 905

% 16.6 17.0 15.3 10.8 6.7 6.2

No. 1,985 3,209 3,302 548 113 700

296,082

42,649

14.4

9,857

3.6 3.0 5.0 3.0 0.3 4.8

MODERATELY & SEVERELY UNDERWEIGHT Eligible No. % Population 11,133 20.2 56,432 21,477 19.9 110,142 13,356 20.3 68,165 2,526 13.7 18,902 2,409 7.0 35,720 1,605 11.0 15,149

3.3

52,506

%

Notes: # -no data * - 1st qtr. Report Only Source: DOH, Field Health Services and Information Systems (FHSIS), Manila.

17.7

** - 2nd qtr. Report Only *** -3rd qtr. Report Only

304,511

MODERATELY UNDERWEIGHT

1997 SEVERELY UNDERWEIGHT

No. 5,858 19,497 14,956 1,287 3,527 1,273

% 10.4 17.7 21.9 6.8 9.9 8.4

1,128 3,741 2,224 282 454 876

2.0 3.4 3.3 1.5 1.3 5.8

MODERATELY & SEVERELY UNDERWEIGHT Eligible No. % Population 6,986 12.4 57,809 23,238 21.1 112,676 17,180 25.2 70,510 1,569 8.3 19,420 3,981 11.1 36,992 2,149 14.2 15,784

46,398

15.2

8,705

2.9

55,103

18.1

313,190

MODERATELY UNDERWEIGHT

25,204

No. 3,961 11,380 6,087 1,013 2,075 688

%

1998 SEVERELY UNDERWEIGHT

6.9 10.1 8.6 5.2 5.6 4.4

No. 594 1,637 1,553 216 321 246

% 1.0 1.5 2.2 1.1 0.9 1.6

8.0

4,567

1.5

% CHANGE IN NUMBER OF % CHANGE IN PROPORTION O MODERATELY & MODERATELY & SEVERELY MODERATELY & SEVERELY SEVERELY UNDERWEIGHT UNDERWEIGHT UNDERWEIGHT No. % 1996-1997 1997-1998 1996-1997 4,555 7.9 -37.2 -34.8 -38.7 13,017 11.6 8.2 -44.0 5.8 7,640 10.8 28.6 -55.5 24.4 1,229 6.3 -37.9 -21.7 -39.5 2,396 6.5 65.3 -39.8 59.6 934 5.9 33.9 -56.5 28.5 29,771

9.5

4.9

-46.0

2.0

% CHANGE IN PROPORTION OF MODERATELY & SEVERELY UNDERWEIGHT 1997-1998

21.8 63.0 -27.9 17.3 -7.8 -49.9 169.9 7.6

-71.0 -57.6 -67.0 -49.0 113.5 -12.2 -83.3 -37.4 215.0 -60.7

% CHANGE IN PROPORTION OF MODERATELY & SEVERELY UNDERWEIGHT 1997-1998 -47.6 -18.4 -54.8 -22.1 -2.1 43.8 706.4 -34.5 -99.6 -42.8 10.1 18.5 -28.5 -59.5 -100.0 105.0 14.3 -1.8 -42.2

% CHANGE IN PROPORTION OF MODERATELY & SEVERELY UNDERWEIGHT 1997-1998

-48.6 11.3 45.9 -11.1 374.4 610.5 -55.1 -7.8 173.9 -2.4 -32.2 -62.3 3.0 1.1

-17.4 -46.1 -39.5 -71.6 -18.4 -38.3 458.5 -72.8 -36.3 -29.2

% CHANGE IN PROPORTION OF MODERATELY & SEVERELY UNDERWEIGHT 1997-1998 -36.4 -45.2 -57.0 -23.8 -41.9 -58.3 -47.5

Table V.27 CONTRACEPTIVE PREVALENCE RATE FOR CURRENTLY MARRIED WOMENT 15 - 49 YEARS OLD, 1993, 1996-1998 (in Percent) Overall

1993 1996 1997 1998 Source:

40.0 48.1 47.0 46.5

By Type Modern Traditional 24.9 30.2 30.9 28.2

15.1 17.9 16.1 18.3

By Locality Urban Rural 43.0 50.7 50.0 50.7

36.8 45.5 44.1 42.2

1993 National Demographic Survey, NSO and Macro Int'l 1996, 1997 Family Planning Survey, NSO 1998 National Demographic and Health Survey, NSO and Macro Int'l

TABLE V.28 FAMILY PLANNING PROGRAM PERFORMANCE, 1996 - 1998 (Unit: Number of Persons)

Province/City

1996 New Acceptors Current Users

1997 New Acceptors Current Users

1998 New Acceptors Current Users

Percentage Change New Acceptors Current Users 1996-1997 1997-1998 1996-1997 1997-1998

NCR 1s Dist. Mun. Manila 2nd Dist. Mun. Quezon City 3rd Dist. Mun. Caloocan City 4th Dist Mun. Pasay City Makati City

17,846 28,756 15,894 47,405 5,256 16,022 16,839 8,388 15,242

21,891 32,235 33,774 88,636 24,444 21,171 27,302 17,175

22,551 24,053 20,362 55,322 27,777 15,995 22,609 8,148

37,238 39,188 40,294 100,467 31,651 18,424 41,385 17,636

20,969 20,497 18,397 44,760 18,320 16,288 20,345 7,033

29,571 20,918 40,242 102,711 29,544 21,087 49,567 17,047

26.4 -16.4 28.1 16.7 428.5 -0.2 34.3 -2.9

-7.0 -14.8 -9.7 -19.1 -34.0 1.8 -10.0 -13.7

41.2 17.7 16.2 11.8 22.8 -14.9 34.0 2.6

-20.6 -46.6 -0.1 2.2 -6.7 14.5 19.8 -3.3

NCR

171,648

266,628

196,817

326,283

166,609

310,687

14.7

-15.3

22.4

-4.8

2,140 1,536 6,554 5,238 2,082 1,619 1,673

5,719 36,366 10,676 5,744 10,706 3,896 4,403

2,166 1,710 5,762 4,718 2,879 1,936 1,997

5,261 14,631 6,504 5,467 3,282 3,642 4,717

2,303 1,499 6,214 4,308 2,001 1,643 2,453

5,221 3,209 13,557 3,273 3,686 2,997 5,348

1.2 11.3 -12.1 -9.9 38.3 19.6 19.4

6.3 -12.3 7.8 -8.7 -30.5 -15.1 22.8

-8.7 -148.6 -64.1 -5.1 -226.2 -7.0 6.7

-0.8 -78.1 108.4 -40.1 12.3 -17.7 13.4

20,842

77,510

21,168

43,504

20,421

37,291

1.6

-3.5

-78.2

-14.3

Ilocos Norte Ilocos Sur La Union Pangasinan Dagupan City Laoag City San Carlos City

4,571 6,621 7,428 29,287 1,048 1,409 2,059

21,381 22,271 23,428 78,477 4,173 5,571 3,302

5,320 11,089 7,206 31,264 1,107 1,422 3,325

18,581 82,608 30,156 85,594 17,165 4,585 3,650

2,370 3,344 3,439 17,905 487 558 1,532

36,673 19,165 26,898 76,111 4,659 4,699 3,382

16.4 67.5 -3.0 6.8 5.6 0.9 61.5

-15.1 73.0 22.3 8.3 75.7 -21.5 9.5

Region 1

52,423

158,603

60,733

242,342

29,635

171,587

15.9

34.6

7,197

24,324

5,981

25,304

1,819

31,963

-16.9

3.9

CAR Abra Apayao Benguet Ifugao Kalinga Mt. Province Baguio City CAR Region 1

Region 3 Bataan

Province/City Bulacan Nueva Ecija Pampanga Tarlac Zambales Angeles City Cabanatuan City Olongapo City Palayan City San Jose City Region 3

Percentage Change 1996 1997 1998 New Acceptors Current Users New Acceptors Current Users New Acceptors Current Users New Acceptors Current Users 1996-1997 1997-1998 1996-1997 1997-1998 22,770 63,942 26,344 65,006 13,453 56,789 15.7 1.6 16,006 36,526 15,676 31,846 -2.1 -14.7 16,839 26,630 20,026 28,904 11,324 27,031 18.9 7.9 17,999 52,192 17,183 55,278 8,912 48,982 -4.5 5.6 6,218 17,452 4,879 17,704 2,789 16,960 -21.5 1.4 7,208 13,808 1,832 8,172 3,500 7,038 -74.6 -69.0 1,845 6,362 1,906 9,622 737 8,848 3.3 33.9 3,513 4,490 4,608 4,925 1,998 4,698 31.2 8.8 358 458 706 174 1,435 27.9 537 3,706 485 5174 967 5,812 -9.7 28.4 100,490

249,432

99,378

252,641

45,673

209,556

-1.1

1.3

6,347 19,337 18,101 25,976 2,537 10,365 8,883 9,184 17,760 24,602 1,958 2,521 1,146 1,451 4,769 868 1,574 461 730

6,643 37,772 36,745 172,259 21,289 16,356 24,342 13,982 54,077 43,208 9,594 4,167 1,827 1,966 11,742 7,537 5,115 1,182 1,444

3,936 4,783 25,054 4,160 2,283 1,624 12,546 2,449 11,941 23,618 664 2,804 178 267 3,325 208 365 97 131

8,439 191,939 195,544 79,900 7,389 46,196 29,816 58,936 71,315 42,065 34,196 4,328 6,683 7,176 22,434 39,846 22,947 5,168 6,953

3,834 3,694 27,171 18,735 1,739 2,313 10,566 1,955 3,914 16,477 1,241 3,457 197 149 13,262 1,070 297 122 156

8,128 56,674 237,328 63,302 4,564 16,404 37,844 43,501 36,841 36,933 11,111 5,016 1,652 2,175 3,147 4,157 7,415 1,706 2,108

-38.0 -75.3 38.4 -84.0 -10.0 -84.3 41.2 -73.3 -32.8 -4.0 -66.1 11.2 -84.5 -81.6 -30.3 -76.0 -76.8 -79.0 -82.1

-2.6 -22.8 8.4 350.4 -23.8 42.4 -15.8

158,570 131,626

471,247 403,188

100,433 86,043

881,270 751,019

110,349 104,480

580,006 499,664

-36.7 -34.6

Region 4 Aurora Batangas Cavite Laguna Marinduque Mindoro Occidental Mindoro Oriental Palawan Quezon Rizal Romblon Batangas City Cavite City Lipa City Lucena City Puerto Princessa City San Pablo City Tagaytay City Trece Martires City Region 4 w/ complete records

-3.7 -70.5 21.4 -20.8 -38.2 -64.5 26.9

-30.2 86.9 23.3 10.7 -44.2 298.9 414.4 -18.6 25.8 19.1

21.3 80.3 81.2 -115.6 -188.1 64.6 18.4 76.3 24.2 -2.7 71.9 3.7 72.7 72.6 47.7 81.1 77.7 77.1 79.2

9.9 21.4

46.5 46.3

-34.2 -33.5

-12.2 -67.5 15.9 -75.3 -69.7 -86.0 -89.6 -67.7 -67.0 -69.7

Province/City

1996 New Acceptors Current Users

1997 New Acceptors Current Users

1998 New Acceptors Current Users

Percentage Change New Acceptors Current Users 1996-1997 1997-1998 1996-1997 1997-1998

Region 5 Albay Camarines Norte Camarines Sur Catanduanes Masbate Sorsogon Iriga City Legaspi City Naga City

7,736 9,281 14,390 2,118 8,956 15,069 717 2,201 3,072

35,044 22,893 22,260 3,363 24,004 30,098 8,105 3,535 23,782

15,094 5,592 14,006 8,879 32,593 6,191 1,107 1,688

87,553 17,661 139,002 13,996 36,974 59,987 24,408 11,438

7,919 1,454 6,616 1,527 4,222 5,763 373 771

29,851 18,785 36,058 3,850 11,331 15,340 5,489 3,802

95.1 -39.7 -2.7 319.2 263.9 -58.9 54.4 -23.3

149.8 -22.9 524.4 316.2 54.0 99.3 201.1 223.6

Region 5 w/complete records

63,540 58,267

173,084 145,767

85,150 83,462

391,019 379,581

28,645

124,506

34.0 43.2

125.9 160.4

Aklan Antique Capiz Iloilo Negros Occ. Guimaras Bacolod City Bago City Cadiz City Iloilo City La Carlota City Roxas City San Carlos City Silay City Sagay City

4,106 8,056 7,805 17,108 24,570 3,586 3,989 1,904 1,341 2,188 389 1,088 1,476 755

11,274 16,358 20,862 57,863 56,902 5,638 21,114 5,151 5,741 11,560 1,953 2,295 1,739 4,020

6,304 9,244 7,746 17,834 40,749 3,124 4,507 3,629 2,231 2,026 529 518 1,878 1,116 2,572

15,170 18,285 19,969 52,291 52,562 6,260 20,714 7,240 6,164 13,339 2,358 2,301 2,837 4,170 8,962

3,043 3,603 3,293 7,301 11,349 500 4,654 1,045 2,007 1,327 391 210 641 1,403 1,881

14,915 19,217 17,620 38,152 55,750 3,221 20,285 6,348 5,437 13,618 2,239 1,849 2,230 4,649 10,629

53.5 14.7 -0.8 4.2 65.8 -12.9 13.0 90.6 66.4 -7.4 36.0 -52.4 27.2 47.8

34.6 11.8 -4.3 -9.6 -7.6 11.0 -1.9 40.6 7.4 15.4 20.7 0.3 63.1 3.7

Region 6

78,361

222,470

104,007

232,622

42,648

216,169

32.7

4.6

15,709 19,048 16,120 1,045 2,015 796

49,635 56,501 37,275 4,443 4,096 1,954

18,551 29,707 21,121 1,159 2,146 725

48,354 263,285 49,549 4,596 4,457 2,018

19,094 26,301 18,349 865 1,281 826

50,301 72,057 61,035 3,706 5,129 2,674

18.1 56.0 31.0 10.9 6.5 -8.9

Region 6

Region 7 Bohol Cebu Negros Or. Siquijor Bais City Canlaon City

2.9 -11.5 -13.1 -25.4 -40.3 13.9

-2.6 366.0 32.9 3.4 8.8 3.3

4.0 -72.6 23.2 -19.4 15.1 32.5

Province/City Cebu City Danao City Dumaguete City Lapu-Lapu City Mandawe City Tagbilaran City Toledo City Region 7

Percentage Change 1996 1997 1998 New Acceptors Current Users New Acceptors Current Users New Acceptors Current Users New Acceptors Current Users 1996-1997 1997-1998 1996-1997 1997-1998 9,229 17,772 7,216 78,660 5,873 21,949 -21.8 -18.6 342.6 -72.1 1,367 6,688 1,457 26,110 1,190 8,447 6.6 -18.3 290.4 -67.6 888 4,032 1,442 4,870 1,420 4,637 62.4 -1.5 20.8 -4.8 2,609 4,640 3,607 6,070 4,234 8,965 38.3 17.4 30.8 47.7 3,131 13,612 3,470 5,781 2,837 7,381 10.8 -18.2 -57.5 27.7 466 1,866 525 1,844 698 2,201 12.7 33.0 -1.2 19.4 227 3,357 919 3,299 633 2,330 304.8 -31.1 -1.7 -29.4 72,650

205,871

92,045

498,893

83,601

250,812

26.7

-9.2

142.3

-49.7

Region 8 Biliran Leyte Del Norte Leyte Del Sur Eastern Samar Northern Samar Western Samar Calbayog City Ormoc City Tacloban City

2,411 18,094 6,634 3,490 3,285 3,034 2,086 2,989 1,065

12,471 43,266 37,158 6,864 7,764 6,924 4,882 11,079 910

3,031 17,782 5,788 5,559 2,740 2,850 1,975 2,205 917

7,285 51,354 11,495 10,587 5,933 6,877 8,737 8,378 2,106

1,488 3,520 2,328 2,275 2,042 2,399 861 1,110 214

15,896 42,293 11,577 9,967 4,390 6,743 8,933 8,990 1,309

25.7 -1.7 -12.8 59.3 -16.6 -6.1 -5.3 -26.2 -13.9

-41.6 18.7 -69.1 54.2 -23.6 -0.7 79.0 -24.4 131.4

Region 8

43,088

131,318

42,847

112,752

16,237

110,098

-0.6

-14.1

Bukidnon Camiguin Misamis Occidental Misamis Oriental Cagayan De Oro City Gingoog City Oroquieta City Ozamis City Tangub City

18,376 703 2,701 9,785 4,926 1,439 1,485 811 150

222,743 4,937 20,805 50,691 19,871 15,279 5,700 10,084 3,452

19,850 1,116 3,081 9,923 3,747 1,336 1,444 2,785 170

72,383 3,879 11,714 32,874 14,398 15,680 5,107 6,712 3,567

21,844 1,598 876 9,776 4,450 3,113 1,128 2,691 496

284,211 4,400 17,476 37,003 20,213 4,739 5,425 7,153 3,233

8.0 58.7 14.1 1.4 -23.9 -7.2 -2.8 243.4 13.3

Region 10 w/ complete records

40,376 37,675

353,562 332,757

43,452 40,371

166,314 154,600

45,972 45,096

383,853 366,377

11,394 9,882 11,067

31,859 30,173 56,577

13,794 11,197 24,202

30,206 22,608 78,395

6,925 4,095 5,441

34,157 7,764 26,886

Region 10 10.0 43.2

292.6 13.4

-1.5 18.8 133.0 -21.9 -3.4 191.8

-67.5 -21.4 -43.7 -35.1 -27.5 2.6 -10.4 -33.4 3.3

7.6 7.2

5.8 11.7

-53.0 -53.5

130.8 137.0

21.1 13.3 118.7

-49.8 -63.4 -77.5

-5.2 -25.1 38.6

13.1 -65.7 -65.7

12.6 40.4 -69.8 6.2 6.6 -9.4

Region 11 South Cotabato Davao Oriental Davao Del Norte

Province/City Sarangani Davao Del Sur Davao City General Santos City Region 11

Percentage Change 1996 1997 1998 New Acceptors Current Users New Acceptors Current Users New Acceptors Current Users New Acceptors Current Users 1996-1997 1997-1998 1996-1997 1997-1998 7,719 25,467 8,382 24,695 4,743 26,195 8.6 -43.4 -3.0 6.1 19,064 48,457 19,202 49,107 4,075 2,927 0.7 -78.8 1.3 -94.0 16,221 47,385 24,752 50,857 12,170 50,602 52.6 -50.8 7.3 -0.5 8,097 36,536 11,126 15,132 4,925 13,343 37.4 -55.7 -58.6 -11.8 83,444

276,454

43,917

271,000

42,404

161,874

-47.4

-3.4

-2.0

Region 12 Lanao Del Norte North Cotabato Sultan Kudarat Cotabato City Iligan City Marawi City

6,476 15,564 10,611 3,333 982 104

15,512 43,756 21,690 6,090 12,276 222

7,160 19,045 13,238 2,425 1,726 323

11,904 46,355 28,042 2,830 17,498 368

3,225 12,330 9,422 1,272 622 135

14,934 42,982 22,299 2,573 17,551 135

10.6 22.4 24.8 -27.2 75.8 210.6

-23.3 5.9 29.3 -53.5 42.5 65.8

Region 12

37,070

99,546

43,917

106,997

27,006

100,474

18.5

7.5

Notes: # -no data * - 1st qtr. Report Only ** - 2nd qtr. Report Only *** -3rd qtr. Report Only Source: DOH, Field Health Services and Information Systems (FHSIS), Manila.

-40.3

TABLE V.29 REASONS FOR CHANGING SCHOOL BY TYPE OF COMMUNITY, JANUARY 1999 ( In Percent ) Reason All Reasons Financial reason Graduation to higher grade Change of residence

Commercial

Upland

100.0 8.3 75.0 16.7

Source :Social Impact of the Regional Financial Crisis, Household Survey.

100.0 40.0 60.0 -

Sustenance 100.0 40.0 60.0 -

Fishing 100.0 40.0 50.0 10.0

Middle Income 100.0 25.0 10.0 65.0

Urban Poor 100.0 55.6 33.3 11.1

Table V.30 PERCENTAGE CHANGE IN ELEMENTARY ENROLLMENT BY REGION, 1996 - 1999

Percentage Change

Region I II III IV V VI VII VIII IX X XI XII XIII NCR CAR ARMM Total

1996-97 to 1997-98 Public Private Grade I Total (I-VI) Grade I Total (I-VI)

Public Grade I Total (I-VI)

1997-98 to 1998-99 Private Grade I Total (I-VI)

Total Grade I Total (I-VI)

-3.34 -3.05 0.00 0.76 0.55 -2.19 -3.50 3.60 0.41 -0.91 12.23 -21.61 2.13 1.22 -1.55 2.05

0.84 2.37 2.84 4.87 1.56 4.19 0.54 2.14 2.74 4.66 15.59 -19.91 4.08 3.54 2.47 4.51

3.98 -2.32 5.45 5.90 -2.61 11.78 -1.34 -2.14 19.96 -7.27 19.89 10.46 16.80 0.44 -5.99 94.84

3.99 3.02 6.93 7.24 0.10 11.47 3.23 1.01 18.41 -1.61 22.68 14.60 6.08 1.87 -7.88 32.62

-2.99 -3.03 0.43 1.22 0.48 -1.72 -3.39 3.51 0.77 -1.17 12.68 -20.50 2.48 1.05 -1.86 2.53

0.99 2.39 3.19 5.09 1.52 4.50 0.68 2.12 3.12 4.36 16.04 -18.45 4.13 3.13 1.58 4.75

-3.55 -1.55 -1.71 -2.06 -1.60 -4.69 -2.70 -4.40 -4.69 -6.31 -1.62 0.10 -5.57 -1.02 -7.10 -3.52

-0.07 1.46 2.51 1.03 1.42 -2.09 6.20 1.80 2.71 -1.88 1.93 -0.45 1.48 2.78 1.23 4.18

-3.19 -1.45 55.53 3.33 -22.98 -41.64 -18.02 -5.57 -26.49 -43.10 -46.62 -29.73 -22.96 -20.79 -1.91 -30.92

2.63 4.34 13.99 7.27 -21.43 -36.63 -5.03 3.60 -24.09 -37.16 -46.90 -27.34 -8.08 -15.99 -3.39 3.05

-3.54 -1.54 3.07 -1.56 -2.09 -6.12 -3.49 -4.41 -5.18 -7.69 -4.43 -1.33 -6.05 -5.48 -6.75 -3.79

0.06 1.56 3.54 1.63 0.80 -3.64 5.59 1.84 1.95 -3.49 -1.36 -2.05 1.21 -1.77 0.87 4.16

-0.22

3.07

4.33

5.59

0.08

3.26

-2.88

1.58

-10.07

-10.33

-3.37

0.67

* as of August 31, 1998 Source: DECS

Total Grade I Total (I-VI)

TABLE V.31 PERCENTAGE CHANGE IN SECONDARY EDUCATION BY REGION, 1996-1999 Percentage Change

Region I II III IV V VI VII VIII IX X XI XII XIII NCR CAR ARMM

Public 1st year Total (I-IV)

1996-97 to 1997-98 Private 1st year Total (I-IV)

Total 1st year Total (I-IV)

Public 1st year Total (I-IV)

1997-98 to 1998-99 Private 1st year Total (I-IV)

Total 1st year Total (I-IV)

-0.36 1.47 3.09 4.07 1.64 -0.08 6.27 4.40 -6.41 10.23 13.80 -15.63 12.77 -0.08 -1.78 21.15

1.65 3.70 4.08 2.88 -1.87 0.44 7.71 0.27 -8.32 6.59 12.09 -18.10 11.37 0.23 -2.81 13.71

-4.80 -9.86 -4.91 -2.81 -12.22 -5.30 -1.15 -6.60 11.59 -10.96 8.60 -28.91 -2.07 -4.39 -11.31 5.70

-3.67 -5.98 -4.77 -1.54 -10.24 -3.69 -0.48 -4.41 20.29 -7.05 14.40 -18.10 1.60 -3.07 -7.26 -0.08

-1.24 -1.08 0.46 1.89 -1.14 -1.01 4.20 2.71 -3.78 3.59 12.71 -19.23 9.50 -1.48 -4.69 18.33

0.48 1.19 0.82 1.35 -3.80 -0.37 5.00 -0.56 -3.46 1.80 12.67 -18.10 8.91 -0.94 -4.27 10.91

-9.02 -27.87 -22.89 -1.55 -0.77 -21.23 0.92 -17.97 -10.67 -7.97 3.60 -1.65 -5.17 -1.30 -9.30 -1.42

-8.64 -27.61 -21.86 0.05 1.54 -19.19 4.22 -16.32 -4.73 -2.42 6.18 1.31 -7.42 -0.30 -5.90 9.68

-8.87 -5.21 -2.85 -5.17 -15.36 -43.88 -2.51 -5.73 -38.20 -2.52 -55.74 -28.10 -5.33 -10.04 3.49 -5.36

-9.63 -6.76 -3.09 -4.36 -13.75 -34.37 -2.39 -7.19 -36.54 -2.83 -56.30 -28.88 -5.09 -8.95 5.78 7.75

-8.99 -23.22 -16.66 -2.64 -3.38 -25.09 0.01 -16.26 -15.33 -6.50 -8.43 -7.96 -5.20 -4.06 -5.66 -2.06

-8.85 -22.59 -15.31 -1.44 -1.75 -22.07 2.15 -14.77 -11.46 -2.55 -9.66 -7.42 -6.88 -3.30 -2.18 9.33

2.62

1.93

-4.87

-2.61

0.70

0.62

-8.17

-6.27

-13.01

-12.10

-9.35

-7.90

Total

* as of August 31 Source: DECS

TABLE V.32 ELEMENTARY DROP-OUT RATE BY REGION BY REGION, 1995-1998 (In Percent)

Region

Public

I II III IV V VI VII VIII IX X XI XII XIII NCR CAR ARMM Total

Source: DECS

1995-1996 Private

Total

Public

Level 1996-1997 Private

Total

Public

1997-98 Private

Total

Percentage Change 1995-96 to 1996-97 1996-97 to 1997-98 Public Private Total Public Private Total

3.26 7.10 4.22 4.72 7.08 10.20 7.52 9.25 10.82 6.66 8.72 11.29 11.70 4.11 7.77 22.96

4.50 7.07 3.39 2.25 10.94 3.22 4.03 7.56 5.35 14.95 3.13 3.55 12.27 0.43 6.93 3.54

3.18 7.09 4.15 4.50 7.19 9.92 7.35 9.22 10.68 7.10 8.37 10.97 11.72 3.17 7.69 22.80

4.77 7.42 4.99 6.91 8.26 10.16 5.75 11.50 13.21 9.92 9.85 12.40 7.51 4.61 6.98 21.10

4.59 0.07 2.76 3.44 3.84 2.77 9.42 3.96 1.57 4.20 8.88 6.87 5.05 3.81 2.24 7.48

4.76 7.20 4.79 6.59 8.14 9.87 5.96 11.38 12.96 9.65 9.79 12.17 7.44 4.41 6.58 20.98

4.71 6.83 5.24 4.39 7.00 7.39 9.32 10.65 12.69 8.03 10.33 9.60 8.15 4.51 7.64 19.79

4.48 5.64 1.90 1.80 5.29 6.25 6.98 8.37 4.61 8.04 1.58 1.50 6.09 3.90 12.72 23.69

4.70 6.79 4.95 4.15 6.96 7.34 9.19 10.61 12.51 8.03 9.78 9.26 8.09 4.36 8.07 19.82

46.32 4.51 18.25 46.40 16.67 -0.39 -23.54 24.32 22.09 48.95 12.96 9.83 -35.81 12.17 -10.17 -8.10

2.00 -99.01 -18.58 52.89 -64.90 -13.98 133.75 -47.62 -70.65 -71.91 183.71 93.52 -58.84 786.05 -67.68 111.30

49.69 1.55 15.42 46.44 13.21 -0.50 -18.91 23.43 21.35 35.92 16.97 10.94 -36.52 39.12 -14.43 -7.98

7.66

2.90

7.31

8.37

4.22

8.06

7.70

3.93

7.42

9.27

45.52

10.26

-1.26 -2.40 -7.95 7957.14 5.01 -31.16 -36.47 -47.67 -15.25 37.76 -27.26 125.63 62.09 -25.90 -7.39 111.36 -3.94 193.63 -19.05 91.43 4.87 -82.21 -22.58 -78.17 8.52 20.59 -2.17 2.36 9.46 467.86 -6.21 216.71 -8.00

-6.87

-1.26 -5.69 3.34 -37.03 -14.50 -25.63 54.19 -6.77 -3.47 -16.79 -0.10 -23.91 8.74 -1.13 22.64 -5.53 -7.94

TABLE V.33 SECONDARY DROP-OUT RATE BY REGION, 1995 - 1998 ( In Percent )

Region

Public

1995-1996 Private

Total

Public

Level 1996-1997 Private

Total

Public

1997-98 Private

Total

Percentage Change 1995-96 to 1996-97 1996-97 to 1997-98 Public Private Total Public Private Total

I II III IV V VI VII VIII IX X XI XII XIII NCR CAR ARMM

6.38 9.74 9.21 8.14 16.01 9.07 7.12 14.94 14.29 17.39 11.61 14.38 16.31 7.00 7.18 14.14

9.06 5.09 6.49 6.91 8.03 4.52 4.00 10.14 11.11 9.04 10.52 3.60 12.88 3.80 5.81 6.97

7.03 8.37 8.12 7.68 14.02 8.16 5.97 14.04 13.67 14.34 11.34 11.28 15.48 5.75 6.67 12.75

7.29 6.50 9.99 9.42 12.22 13.25 12.27 13.37 8.03 14.02 12.47 13.59 10.43 6.86 14.93 20.93

4.35 4.95 8.45 7.35 9.34 6.11 14.22 10.51 5.32 6.47 2.29 11.61 5.62 10.73 6.76 1.21

6.62 6.07 9.40 8.68 11.51 11.83 12.98 12.86 7.55 11.36 10.00 12.97 9.20 8.32 12.22 16.81

7.83 6.88 9.91 14.52 14.14 8.40 9.53 15.29 26.53 11.68 17.61 9.66 11.36 10.33 14.76 15.79

6.12 6.07 7.38 5.30 14.13 9.23 6.31 8.44 4.13 11.11 8.83 2.18 4.74 4.80 12.62 17.48

7.46 6.67 9.00 11.40 14.14 8.56 8.50 14.10 22.89 11.48 15.52 7.44 9.74 8.43 14.05 16.13

14.26 -33.26 8.47 15.72 -23.67 46.09 72.33 -10.51 -43.81 -19.38 7.41 -5.49 -36.05 -2.00 107.94 48.02

-51.99 -2.75 30.20 6.37 16.31 35.18 255.50 3.65 -52.12 -28.43 -78.23 222.50 -56.37 182.37 16.35 -82.64

-5.83 -27.48 15.76 13.02 -17.90 44.98 117.42 -8.40 -44.77 -20.78 -11.82 14.98 -40.57 44.70 83.21 31.84

Total

10.31

6.49

9.11

10.60

8.27

9.90

12.25

7.00

10.76

2.81

27.43

8.67

Source: DECS

7.41 40.69 5.85 22.63 -0.80 -12.66 54.14 -27.89 15.71 51.28 -36.60 51.06 -22.33 -55.63 14.36 -19.70 230.39 -22.37 -16.69 71.72 41.22 285.59 -28.92 -81.22 8.92 -15.66 50.58 -55.27 -1.14 86.69 -24.56 1344.63 15.57

-15.36

12.69 9.88 -4.26 31.34 22.85 -27.64 -34.51 9.64 203.18 1.06 55.20 -42.64 5.87 1.32 14.98 -4.05 8.69

TABLE VI.1 DISTRIBUTION OF PERSONS 15 YEARS and OVER WHO CHANGED WORK in the PAST TWO YEARS by PLACE of WORK, ALL COMMUNITY, AS OF JANUARY 1999 ( IN PERCENT ) Previous Place of Work PresentPlace of Work All Sectors Government Private office, banks Factory Informal sector Owner, HH operated Transport/utilities Store, business & personal service Community service(school, hospital) Others

All Sectors 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Government

Private office, banks

2.9

4.4 12.5 20.0

Factory 8.8 20.0

50.0 10.0 10.0

30.0

100.0

12.5

Store, Community Owner, HH Transport / business & service operated utilities personal (school, service hospital) 13.2 8.8 5.9 17.6 5.9 25.0 12.5 20.0 20.0 50.0 10.0 20.0 10.0 20.0 10.0 10.0 33.3 33.3 16.7

Informal sector

18.8

100.0 100.0

6.3 20.0 16.7

25.0

Others 32.4 50.0 20.0 30.0 40.0 16.7 37.5

20.0 33.3

60.0

Store, business & personal service 100.0

Community service (school, hospital) 100.0 25.0

50.0

Previous Place of Work PresentPlace of Work All Sectors Government Private office, banks Factory Informal sector Owner, HH operated Transport/utilities Store, business & personal service Community service(school, hospital) Others

All Sectors 100.0 11.8 7.4 2.9 14.7 14.7 8.8

Private Government office, banks 100.0

100.0 33.3 33.3

Factory 100.0

100.0

16.7

11.1 11.1 11.1 11.1 22.2

50.0 33.3 50.0

23.5 7.4 8.8

Source :Social Impact of the Regional Financial Crisis, Household Survey.

Informal sector

50.0

33.3

Owner, HH operated

Transport / utilities

100.0 33.3

100.0

33.3

33.3 16.7 16.7

Others

8.3

100.0 18.2 4.5

50.0

16.7 8.3 8.3

13.6 18.2 4.5

25.0

33.3

27.3

25.0

8.3 16.7

75.0 13.6

TABLE VI.2 DISTRIBUTION OF PERSONS 15 YEARS AND OVER WHO CHANGED WORK IN THE PAST TWO YEARS

BY PLACE OF WORK AND TYPE OF COMMUNITY, AS OF JANUARY 1999 ( IN PERCENT) Place of Work All Sector Government Private office, bank Factory Informal sector Owner, household operated Transport, utilities Store, business & personal service Community services (school, hospital) Others, n.e.c.

Farming Former Present 100.0 3.8 7.7 3.8 7.7 7.7 7.7 23.1 3.8 34.6

Source :Social Impact of the Regional Financial Crisis, Household Survey.

100.0 11.5 7.7 7.7 7.7 11.5 11.5 26.9 15.4

Fishing Former Present 100.0 9.1 18.2 9.1 63.6

100.0 9.1 9.1 27.3 36.4 18.2

Middle Income Former Present 100.0 4.3 17.4 21.7 4.3 8.7 17.4 13.0 13.0

100.0 4.3 8.7 8.7 26.1 8.7 21.7 21.7 -

Urban Poor Former Present 100.0 17.6 5.9 17.6 5.9 11.8 41.2

100.0 17.6 11.8 23.5 5.9 23.5 17.6

TABLE VI.3 REASONS FOR LEAVING LAST JOB, ALL COMMUNITIES, JANUARY 1999 Reason All Reasons Retrenched/dismissed/closure Seasonal Desire to change work Change of residence For better pay/stability in job Others

Percent 100.0 15.1 9.6 24.7 12.3 20.5 17.8

TABLE VI.4 REASONS FOR THE RETURN OF MIGRANT HOUSEHOLD MEMBER, ALL COMMUNITIES, JANUARY 1999 Reason Completion of contract Others Termination/retrenchment

Percent 42.9 48.2 8.9

TABLE VI.5 REASONS FOR THE RETURN OF MIGRANT FAMILY MEMBER

BY TYPE OF COMMUNITY, JANUARY 1999 Reason Completion of contract Termination; retrenchment Vacation Job dissatisfaction Others

Commercial 100.0 50.0

16.7 33.3

Upland 100.0

Sustenance

16.7 33.3

100.0 47.4 10.5 36.8

100.0 33.3 11.1 33.3

50.0

5.3

22.2

TABLE VI.6 DISTRIBUTION OF HOUSEHOLDS GETTING FINANCIAL SUPPORT FROM MIGRANT FAMILY MEMBERS BY PERCENT SHARE TO TOTAL HOUSEHOLD INCOME, ALL COMMUNITIES, JANUARY 1999 Share to Household Income Total at most 5% over 5-10% over 10-25% over 25-50% over 50-75% over 75%

Fishing

Percent 100.0 12.2 18.4 15.3 26.5 13.3 14.3

Source of the four tables: Social Impact of the Regional Financial Crisis, Household Survey.

Middle Income 100.0 85.7

14.3

Urban Poor 100.0 33.3 11.1 11.1 22.2 22.2

TABLE VI.7 IMPACT ON FAMILIES OF MIGRANT WORKERS, JANUARY 1999 (Percent of Communities) Impact Return to home because Loss of job Finished contract Not satisfied with working conditions Family/personal reasons Deterioration of social fiber Better living conditions Repair, renovation or construction of residences Establish business, investment Source of credit Contribute to community projects Attraction to work abroad

All Communities

Middle Income

8 10 8

Urban Poor

14

Fishing

Farming

25 13 13

18 18 9

2

5

14

15

43

13

5

36 28

38 8

57 43

38 38

27 32

6

14

2 16

29

25

5 18

43

13

27

22

8

9

Source: Social Impact of the Regional Financial Crisis, Household Survey.

TABLE VI.8 HOUSEHOLDS RESPONSE TO EMPLOYMENT AND LABOR MARKET PROBLEMS, JANUARY 1999 (Percent of Communities) Response Increased child labor Working housewives Seek employment elsewhere Shift to home-based operation

Middle Income 31 46 15 8

Urban Poor 71 29 14 14

Fishing

Farming

75 50 25 13

59 18 18 9

Source: Social Impact of the Regional Financial Crisis, Household Survey.

TABLE VI.9 PERCENT CHANGES IN HOUSEHOLD BUDGETING AND POVERTY AND WELL-BEING ASSESSMENT BY TYPE OF COMMUNITY, 1997-1998 Commercial

Upland

Sustenance

Fishing

Middle Income

Urban Poor

48.0 46.3

49.5 53.3

50.7 50.4

49.9 52.0

38.5 40.4

46.4 46.7

11.6 11.8

9.8 10.3

13.1 13.7

10.9 11.4

9.4 9.5

7.1 7.2

8.8 7.8

8.1 8.5

8.8 8.4

8.7 9.1

7.3 7.9

6.9 7.4

2.9 2.9

2.9 3.1

2.9 2.8

5.1 5.3

9.1 9.5

4.5 4.6

6.9 6.3

7.5 6.0

8.1 6.7

5.1 4.1

6.8 6.4

7.5 5.9

6.3 5.7

6.6 6.9

7.9 8.1

6.7 7.1

7.6 8.3

7.4 7.1

1.3 1.4

0.5 0.6

3.2 2.0

3.1 1.6

4.3 3.1

3.4 2.8

Poverty Assessment Poor now Poor in '97 Middle income in'97 Rich in '97 Middle income now Poor in '97 Middle income in '97 Rich now and '97 No reply

31.7 94.7 5.3 65.0 5.1 94.9 3.3

60.0 83.3 16.7 36.7 100.0 3.3

41.7 100.0 56.7 100.0 1.7

69.5 87.8 12.2 27.1 12.5 87.5 3.4

20.8 76.2 19.0 4.8 76.2 1.3 98.7 1.0 2.0

47.8 95.3 4.7 50.0 2.2 97.8 2.2

Self rating of change in well-being Worst Worse Bad Neutral Good Better Much improved

8.3 11.7 10.0 41.7 23.3 5.0 -

20.0 20.0 21.7 23.3 11.7 3.3 -

1.7 11.7 20.0 51.7 10.0 1.7 3.3

5.1 11.9 35.6 22.0 16.9 8.5 -

4.0 4.0 11.9 25.7 30.7 16.8 6.9

12.2 12.2 18.9 24.4 24.4 7.8 -

Item Household Budget Food 1997 1998 Education 1997 1998 Medical 1997 1998 Housing 1997 1998 Clothing 1997 1998 Transportation 1997 1998 Leisure 1997 1998

Source: Social Impact of the Regional Financial Crisis, Household Survey.

TABLE VI.10 INFORMATION ON CREDIT AND SAFETY NETS, ALL COMMODITIES JANUARY 1999 Item Availed credit Availment level More at most 10% up to 25% up to 50% over 50% Less at most 10% up to 50% over 50% Same Availment of safety net Financial assistance DSWD Free food Subsidized food Free vaccination Free or subsidized farm input Employed in public works projects

Percent 63.0 100.0 44.2 20.8 34.0 34.0 11.3 9.2 31.8 45.5 22.7 46.7

12.8 20.7 18.6 45.6 10.7

Item

Percent

Source of credit Friends, relatives 5/6lenders Banks Traders Others

46.5 23.6 25.5 4.4 11.1

utilization of credit Production House repair Augmentation of income School expenses Medical expenses Acquisition of capital Goods Gambling Others

15.5 15.5 32.1 26.9 21.4 19.2 0.4 14.0

Adequacy of safety nets

17.9

4.7

Source: Social Impact of the Regional Financial Crisis, Household Survey.

TABLE VI.11 INFORMATION ON CREDIT AND SAFETY NETS BY TYPE OF COMMUNITY, JANUARY 1999 Item

Middle Income

Commercial

Upland

Sustenance

Fishing

65.0

45.0

70.0

64.4

70.3

60.0

100.0 45.2 14.3 50.0 28.6 7.1 6.5 100.0 48.4

100.0 52.2 16.7 33.3 25.0 25.0 8.7 50.0 50.0 39.1

100.0 62.2 26.1 21.7 34.8 17.4 10.8 25.0 50.0 25.0 27.0

100.0 42.4 21.4 42.9 35.7 6.1 50.0 50.0 51.5

100.0 33.3 22.7 22.7 36.4 18.2 10.6 28.6 42.9 28.6 56.1

100.0 42.0 19.0 42.9 38.1 10.0 60.0 20.0 20.0 48.0

Source of credit Friends, relatives 5/6 lenders Banks, financial institutions Traders Others

38.5 2.6 35.9 7.7 28.2

51.9 7.4 18.5 7.4 14.8

52.4 2.4 38.1 9.5

55.3 36.8 10.5 15.8

39.4 35.2 35.2 2.8

48.1 38.9 9.3 13.0 5.6

Utilization of credit Production Augmentation of income School expenses Medical expenses House repair Acquisition of capital goods Gambling Others

38.5 15.4 25.6 23.1 20.5 5.1 23.1

37.0 3.7 40.7 22.2 29.6 3.7 3.7

28.6 16.7 33.3 33.3 19.0 11.9 9.5

5.3 55.3 44.7 34.2 15.8 28.9

2.8 25.4 19.7 19.7 15.5 29.6 11.3

1.9 18.5 31.5 24.1 18.5 31.5 1.9 9.3

Availment of safety nets Financial assistance DSWD Free food Subsidized food Free vaccination Free or subsidized farm input

18.3 30.0 13.3 46.7 13.3

15.0 23.3 16.7 53.3 28.3

15.0 23.3 18.3 56.7 23.3

18.6 27.1 39.0 67.8 5.1

10.9 6.9 6.9 23.8 4.0

4.4 22.2 23.3 42.2 -

3.3

3.3

3.3

5.1

7.9

3.3

21.7

21.7

28.3

22.0

5.9

16.7

Availed credit Availment level More at most 10% up to 25% up to 50% over 50% Less at most 10% up to 50% over 50% Same

Employed in public works projects Adequacy of safety nets

Source: Social Impact of the Regional Financial Crisis, Household Survey.

Urban Poor

TABLE VI.12 PROFILE OF INCOME DISTRIBUTION AND CONSUMPTION OF HOUSEHOLDS, JANUARY 1999 Item Increase in income Decrease in income No change

Percent

Item

Percent

17.0 30.5 52.6

Increase in income At most 5% over 5 - 10% over 10 - 20 over 20 - less than 50% 50% and over

100.0 9.6 26.0 28.8 32.9 2.7

Decrease in income at most 10% over 10 - 20% over 20 - 30% over 30 - 50% over 50%

100.0 16.8 19.8 22.1 28.2 13.0

Reason for increase in income Promotion in job increased in number of earning members New/additional work Favorable price Increased harvest; good weather Availment of credit Winning in gambling Others

100.0 22.2 14.4 12.2 5.6 3.3 2.2 1.1 38.9

Reasons for decrease in income Poor harvest; bad weather Lower price for produce Reduced number or earning members Reduced financial support from relatives Retrenchment Payment of overdue loans Losses in gambling Others

100.0 37.7 17.5 12.0 8.2 6.0 2.2 1.1 15.3

Sale of assets/property yes no

100.0 Reasons for sale of assets 17.4 Augmentation of household income 82.6 Payment of school fee Payment of health service/medicine 100.0 Payment of Loan 21.2 Capital for production/farm 18.2 House repair 18.2 Others 3.0 39.4

Kind of property sold Land Appliance Jewelry House Others

Source: Social Impact of the Regional Financial Crisis, Household Survey.

100.0 51.5 10.6 7.6 4.5 3.0 3.0 19.7

TABLE VI.13 INCOME DISTRIBUTION PROFILE OF HOUSEHOLDS BY TYPE OF COMMUNITY JANUARY 1999 Item

Middle Income 100.0 58.4 22.8 34.8 43.5 21.7 18.8 31.6 15.8 36.8 15.8

Commercial

Upland

Sustenance

Fishing

Change in household income no change Increase in income at most 10% up to 20% up to 50% over 50% Decreased at most 10% up to 20% upto 30% up to 50% over 50%

100.0 50.0 23.3 35.7 21.4 42.9 26.7 18.8 12.5 31.3 31.3 6.3

100.0 41.7 8.3 40.0 40.0 20.0 50.0 20.0 3.3 13.3 43.3 20.0

100.0 46.7 13.3 37.5 12.5 50.0 40.0 16.7 25.0 20.8 16.7 20.8

100.0 55.9 11.9 28.6 28.6 42.9 32.2 10.5 31.6 26.3 21.1 10.5

Cause of increase in income promotion in job goo weather favorable prices new work increased financial support winning in gambling availability of credit

100.0 22.2 11.1 22.2 22.2 22.2 -

100.0 25.0

100.0 25.0 25.0 50.0 -

100.0 61.1

100.0 21.4

25.0 25.0 25.0 -

100.0 33.3 16.7 16.7 33.3 -

5.6 16.7 11.1 5.6

7.1 28.6 35.7 7.1

100.0 4.00 60.00 32.00

100.0 2.33 58.14 27.91

100.0 51.35 29.73

100.0 11.11 77.78 -

100.0 11.11 -

100.0 26.09 13.04 4.35

4.00 -

6.98 2.33 2.33 -

10.81 5.41 2.70

11.11 -

61.11 16.67 5.56 5.56

13.04 34.78 8.70 -

13.3 100.0 22.2 77.8

18.3 100.0 9.1 18.2 72.7

21.7 100.0 20.0 80.0

10.2 100.0 25.0 25.0 25.0 25.0 -

20.8 100.0 33.3 27.8 27.8 11.1

17.8 100.0 7.1 14.3 42.9 28.6 7.1

55.6 22.2

54.5 18.2

50.0 30.0

50.0 -

55.6 -

42.9 -

Cause of decrease in income retrenchment poor harvest lower prices for produce reduction in working members reduction in remittances payment of overdue loans losses in gambling Sold asset Asset sold House land Jewelry Appliance Animals Reasons for sale of assets Augmentation of income Payment of school fees Payment for health service; medicine Payment of loan Capital for production/farm House repair Others

22.2

18.2 9.1 -

Source: Social Impact of the Regional Financial Crisis, Household Survey.

10.0 10.0

25.0 25.0

5.6 38.9

Urban Poor 100.0 56.7 17.8 37.5 31.3 25.0 6.3 25.6 30.4 21.7 30.4 17.4 -

21.4 14.3 7.1 14.3

Table VII.1. LIST OF AVAILABLE INDICATORS Indicators

Disaggregation

Employment Labor Force National, Regional

by Employment Status

by Major Occupation Group

by Major Industry Group Employed Person by class of workers Overseas Filipino Workers Deployment Remmittance Minimum Wage Rate

Source

Frequency of Data

Schedule of Data

Collection

Release

Labor Force Survey from the Every quarter five months after the conduct National Statistics Office (NSO) (Jan, April, July, Oct) of the survey (May, Aug, Nov, Feb)

by Country of Destination Philippine Overseas Employment Every month Administration(POEA)

by Country of Destination/ Selected Philippine Economic Every month

by Type of Worker Indicators (SPEI) from the BSP

three months after the reference month two months after the reference month

National, Regional,

National Wage and Productivity Every month Commission (NWPC)

National, Regional,

by Urbanity

National Statistical Coordination Board (NSCB)

Every three years (1991, 1994, 1997 )

National

National Income Accounts from the NSCB

Every quarter Two months after the reference quarter (Jan, April, July, Oct) (May, August, November, February)

Regional

Gross Regional Domestic Product from the NSCB

Every year

Seven Months after the reference year

Prices of basic commodities

National, Regional

Every month

One week after the reference month

Consumer Price Index

National, Regional

Bureau of Agricultural Statistics (BAS) NSO

Every month

Five days after the reference month (July)

Poverty Incidence Poverty Threshold Poverty Incidence Magnitude of the Poor Subsistence Threshold Subsistence Incidence Magnitude of the Subsistence National Accounts Gross Domestic Product Gross Regional Domestic Product

One year after the reference year

Indicators

Disaggregation

Housing Housing and Housing CharacteristicsNational, Regional, Tenure Status Provincial, by urbanity Roofing Materials Wall Materials Housing Convenience National, Regional, Electricity by urbanity Source of drinking water Time to get to water source Sanitation Facility Flooring Persons per sleeping room Mean persons per room Iodized salt Access to Social Services Access to basic needs : National, Regional, Source of Water Supply Provincial, by urbanity Electricity Toilet Facility Ownership of Durables (Radio, TV, Sala Set, etcâ&#x20AC;Ś) Unduplicated Number of Clients servedNational, Regional, Coverage and Contributions

by GSIS/SSS Benefits Paid by GSIS/SSS Crime Statistics Crimes by Type Index Crimes Non Index Crimes Crime Against Property Crime Against Person Crime Rate

National, Regional Provincial, by Cities

National, Regional

Source

Frequency of Data

Schedule of Data

Collection

Release

Family Income and Expenditure Every three years Survey (FIES) from the NSO (1991, 1994, 1997)

One year after the reference year

National Demographic Survey from the NSO

Every Five years (1988, 1993, 1998)

Four months after the reference year (April)

FIES from the NSO

Every three years (1991, 1994, 1997)

One year after the reference year

Stat Yearbook from the NSCB

Every year

Philippine National Police

Every year

Three months after the reference year

One month after the reference year

Indicators

Enrolment Gross Enrolment Ratio Participation Rate Cohort Survival Rate Retention Rate Graduation Rate Drop out Rate Completion Rate Transition Rate Repetition Rate - Functional Literacy Rate

Health Mortality Rate Infant Mortality Rate Child Mortality Rate Maternal Mortality Rate Leading Causes Number of Crude Death Rate Fertility Rate Current Fertility Fertility Trends Teenage Fertility Family Planning

Disaggregation

Source

Frequency of Data

Schedule of Data

Collection

Release

National, Regional,

by Sex, by type of school (Govt, Private)

Statistics Bulletin from the Department of Education Culture and Sports (DECS)

Every year

Four months after the reference school year (October)

National, Regional, by sex, by age group by urbanity

Functional Literacy Education and Mass Media Survey (FLEMMS) of the NSO

Every Five years (1989, 1994, 1999)

One year after the reference year

National, Regional

National Demographic Survey of the NSO

Every Five years (1988, 1993, 1998)

Four months after the reference year (April)

National, Regional by age, urbanity by marital duration

Indicators

Nutrition Life Expectancy

Disaggregation

National, Regional

Malnutrition National, Regional Percent of Malnourished Children by urbanity Protein Energy Malnutrition (PEM) Deficiency in : Vitamin A Iron and Micronutrients Iodine Mean Per Capita Food Consumption Nutrient Intake Energy Protein Iron and Micronutrients Calcium Retinol Equivalent Thiamin Riboflavin Niacin Ascorbic Acid Fats Carbohydrates

Source: Various Government Agencies.

National, Regional, by urbanity

by Income Quartile

by One-day per Capita Food Peso Value

by HH size

by Occupation of Highest income earner

Source

Frequency of Data

Schedule of Data

Collection

Release

National Demographic Survey of the NSO

Every Five years (1988, 1993, 1998)

Four months after the reference year (April)

National Nutrition Survey from the Food and Nutrition Research Institute (FNRI)

Every five years One year after the reference year (1993, 1988, 1993, 1998)